1. Joint  Access  Control  and  Resource  Allocation  for Concurrent and Massive

Access of M2M Devices

Machine-to-machine (M2M) communications, also known as machine-type communications

(MTC) in 3GPP LTE systems, provide autonomous connectivity between machines without

human intervention to create new service, e.g., the Internet of Things and the smart grid. M2M

communications normally involve a large number of MTC devices (MTCDs) to support a variety

of sensor applications. Consequently, concurrent and massive access attempts of MTCDs to

radio access networks (RANs) may cause intolerable delay, packet loss, and even service

unavailability. In this paper, we propose a joint optimal physical random access channel

(PRACH) resource allocation and access control mechanism to address the performance

degradation caused by concurrent and massive access attempts of MTCDs in LTE systems. We

define the notion of random access efficiency and formulate an optimization problem for

maximization of the random access efficiency with random access delay constraint. We also

propose a dynamic resource allocation and access control algorithm based on estimation of the

number of MTCDs for a system with dynamically varying numbers of massive MTCDs. Then,

an analytical model is provided using a discrete-time Markov chain for the proposed mechanism.

The effectiveness of the proposed algorithm is demonstrated via analysis and simulations. The

proposed algorithm was able to maintain the optimal random access efficiency while satisfying

the average random access delay requirement of MTCDs in order to handle massive and dynamic

MTCDs per cell.

2. Downlink Power Control in Self-Organizing Dense Small Cells Underlaying

Macrocells: A Mean Field Game

A novel distributed power control paradigm is proposed for dense small cell networks co-

existing with a traditional macrocellular network. The power control problem is first modeled as

a stochastic game and the existence of the Nash Equilibrium is proven. Then we extend the

formulated stochastic game to a mean field game (MFG) considering a highly dense network. An

MFG is a special type of differential game which is ideal for modeling the interactions among a

large number of entities. We analyze the performance of two different cost functions for the

mean field game formulation. Both of these cost functions are designed using stochastic

geometry analysis in such a way that the cost functions are valid for the MFG setting. A finite

difference algorithm is then developed based on the Lax-Friedrichs scheme and Lagrange

relaxation to solve the corresponding MFG. Each small cell base station can independently

execute the proposed algorithm offline, i.e., prior to data transmission. The output of the

algorithm shows how each small cell base station should adjust its transmit power in order to

minimize the cost over a predefined period of time. Moreover, sufficient conditions for the

uniqueness of the mean field equilibrium for a generic cost function are also given. The

effectiveness of the proposed algorithm is demonstrated via numerical results.

3. Hybrid Opportunistic Relaying and Jamming With Power Allocation for Secure

Cooperative Networks

This paper studies the cooperative transmission for securing a decode-and-forward (DF) two-hop

network where multiple cooperative nodes coexist with a potential eavesdropper. Under the more

practical assumption that only the channel distribution information (CDI) of the eavesdropper is

known, we propose an opportunistic relaying with artificial jamming secrecy scheme, where a

“best” cooperative node is chosen among a collection of N possible candidates to forward the

confidential signal and the others send jamming signals to confuse the eavesdroppers. We first

investigate the ergodic secrecy rate (ESR) maximization problem by optimizing the power

allocation between the confidential signal and jamming signals. In particular, we exploit the

limiting distribution technique of extreme order statistics to build an asymptotic closed-form

expression of the achievable ESR and the power allocation is optimized to maximize the ESR

lower bound. Although the optimization problems are non-convex, we propose a sequential

parametric convex approximation (SPCA) algorithm to locate the Karush-Kuhn-Tucker (KKT)

solutions. Furthermore, taking the time variance of the legitimate links' CSIs into consideration,

we address the impacts of the outdated CSIs to the proposed secrecy scheme, and derive an

asymptotic ESR. Finally, we generalize the analysis to the scenario with multiple eavesdroppers,

and give the asymptotic analytical results of the achievable ESR. Simulation results confirm our

analytical results.

4. Assessing Performance Gains Through Global Resource Control of Heterogeneous

Wireless Networks

We study the resource allocation and management issues related to heterogeneous wireless

systems made up of several Radio Access Technologies (RATs) that collectively provide a

unified wireless network to a diverse set of users through co-ordination managed by a centralized

Global Resource Controller (GRC). We assume that the user devices are multimodal, which

makes it possible for each device to use any available Access Point (AP)/Base Station (BS) of a

RAT at any given time. Through detailed protocol level simulations performed in ns-2, we show

an increase in spectral efficiency of up to 99% and an increase in short-term fairness of up to

28.5% for two greedy sort-based user device-to-AP/BS association algorithms implemented at

the GRC compared to a distributed solution used in practice today where each user makes his/her

own association decision. While the increase in overhead due to re-associations for a centralized

solution grows only slightly (by up to 4.1%) compared to a distributed solution, we find the

performance increase in spectral efficiency and short-term fairness attributes come at the cost of

an order of magnitude increase (of up to 794%) in energy consumption.

5. Greening Geographical Load Balancing

Energy expenditure has become a significant fraction of data center operating costs. Recently,

“geographical load balancing” has been proposed to reduce energy cost by exploiting the

electricity price differences across regions. However, this reduction of cost can paradoxically

increase total energy use. We explore whether the geographical diversity of Internet-scale

systems can also provide environmental gains. Specifically, we explore whether geographical

load balancing can encourage use of “green” renewable energy and reduce use of “brown” fossil

fuel energy. We make two contributions. First, we derive three distributed algorithms for

achieving optimal geographical load balancing. Second, we show that if the price of electricity is

proportional to the instantaneous fraction of the total energy that is brown, then geographical

load balancing significantly reduces brown energy use. However, the benefits depend strongly on

dynamic energy pricing and the form of pricing used.

6. A Hierarchical Account-Aided Reputation Management  System for MANETs

Encouraging cooperative and deterring selfish behaviors are important for proper operations of

MANETs. For this purpose, most previous efforts either rely on reputation systems or price

systems. However, both systems are neither sufficiently effective in providing cooperation

incentives nor efficient in resource consumption. Nodes in both systems can be uncooperative

while still being considered trustworthy. Also, information exchange between mobile nodes in

reputation systems and credit circulation in price systems consume significant resources. This

paper presents a hierarchical Account-aided Reputation Management system (ARM) to

efficiently and effectively provide cooperation incentives. ARM builds a hierarchical locality-

aware DHT infrastructure for efficient and integrated operations of both reputation and price

systems. The infrastructure helps to globally collect all reputation information in the system,

which helps to calculate more accurate reputation and detect abnormal reputation information.

Also, ARM coordinately integrates resource and price systems by enabling higher-reputed nodes

to pay less for their received services. Theoretical analysis demonstrates the properties of ARM.

Simulation results show that ARM outperforms both a reputation system and price system in

terms of effectiveness and efficiency.

7. Utility Fair Optimization of Antenna Tilt Angles in LTE  Net works

We formulate adaptation of antenna tilt angle as a utility fair optimization task. This optimization

problem is nonconvex, but in this paper we show that, under reasonable conditions, it can be

reformulated as a convex optimization. Using this insight, we develop a lightweight method for

finding the optimal antenna tilt angles, making use of measurements that are already available at

base stations, and suited to distributed implementation.

8. Efficient Allocation Of Periodic Feedback Channels In  Broadband Wireless

Networks

Advanced wireless technologies such as multiple-input–multiple-output (MIMO) require each

mobile station (MS) to send a lot of feedback to the base station. This periodic feedback

consumes much of the uplink bandwidth. This expensive bandwidth is very often viewed as a

major obstacle to the deployment of MIMO and other advanced closed-loop wireless

technologies. This paper is the first to propose a framework for efficient allocation of periodic

feedback channels to the nodes of a wireless network. Several relevant optimization problems are

defined and efficient algorithms for solving them are presented. A scheme for deciding when the

base station (BS) should invoke each algorithm is also proposed and shown through simulations

to perform very well.

9. Proportional Fair Coding For wireless mesh Networks

We consider multihop wireless networks carrying unicast flows for multiple users. Each flow has

a specified delay deadline, and the lossy wireless links are modeled as binary symmetric

channels (BSCs). Since transmission time, also called airtime, on the links is shared among

flows, increasing the airtime for one flow comes at the cost of reducing the airtime available to

other flows sharing the same link. We derive the joint allocation of flow airtimes and coding

rates that achieves the proportionally fair throughput allocation. This utility optimization

problem is nonconvex, and one of the technical contributions of this paper is to show that the

proportional fair utility optimization can nevertheless be decomposed into a sequence of convex

optimization problems. The solution to this sequence of convex problems is the unique solution

to the original nonconvex optimization. Surprisingly, this solution can be written in an explicit

form that yields considerable insight into the nature of the proportional fair joint airtime/coding

rate allocation. To our knowledge, this is the first time that the utility fair joint allocation of

airtime/coding rate has been analyzed, and also one of the first times that utility fairness with

delay deadlines has been considered.

10. Exploiting Asynchronous Amplify-And-Forward Relays To Enhance The

Performance Of Ieee 802.11 Networks

Cooperative communication is a promising path to recover from performance anomaly in IEEE

802.11 networks. However, a simple solution for employing multiple relays to enhance the relay

link quality has not been proposed. The main obstacle for multiple relay utilization in distributed

networks is that synchronizing relay transmissions requires huge signaling overhead. In this

paper, we investigate the problem from both a physical-layer and MAC-layer point of view. In

the physical layer, a simple, practical solution that provides diversity gain from asynchronous

relay transmissions is introduced. In the MAC layer, a rate adaptation algorithm, RA-ARF, that

takes the extra relay path into account is discussed, and R-MAC is designed to utilize relays in

IEEE 802.11 networks. Our simulation results show considerable improvement in network

performance using R-MAC.

11. Cellular Architecture And Key Technologies For 5g Wireless Communication

Networks

The fourth generation wireless communication systems have been deployed or are soon to be

deployed in many countries. However, with an explosion of wireless mobile devices and

services, there are still some challenges that cannot be accommodated even by 4G, such as the

spectrum crisis and high energy consumption. Wireless system designers have been facing the

continuously increasing demand for high data rates and mobility required by new wireless

applications and therefore have started research on fifth generation wireless systems that are

expected to be deployed beyond 2020. In this article, we propose a potential cellular architecture

that separates indoor and outdoor scenarios, and discuss various promising technologies for 5G

wireless communication systems, such as massive MIMO, energy-efficient communications,

cognitive radio networks, and visible light communications. Future challenges facing these

potential technologies are also discussed.

12. Energy-Efficient Sensor Scheduling Algorithm in Cognitive Radio Networks

Employing Heterogeneous Sensors

We consider, in this paper, the maximization of throughput in a dense network of collaborative

cognitive radio (CR) sensors with limited energy supply. In our case, the sensors are mixed

varieties (heterogeneous) and are battery powered. We propose an ant colony-based energy-

efficient sensor scheduling algorithm (ACO-ESSP) to optimally schedule the activities of the

sensors to provide the required sensing performance and increase the overall secondary system

throughput. The proposed algorithm is an improved version of the conventional ant colony

optimization (ACO) algorithm, specifically tailored to the formulated sensor scheduling problem.

We also use a more realistic sensor energy consumption model and consider CR networks

employing heterogeneous sensors (CRNHSs). Simulations demonstrate that our approach

improves the system throughput efficiently and effectively compared with other algorithms

13. Opportunistic Spectrum Access with Two Channel Sensing in Cognitive Radio

Networks 14 Optimal Scheduling for Multi-Radio Multi-Channel Multi-Hop

Cognitive Cellular Networks

In cognitive radio networks, spectrum sensing is a critical to both protecting the primary users

and creating spectrum access opportunities of secondary users. Channel sensing itself, including

active probing and passive listening, often incurs cost, in terms of time overhead, energy

consumption, or intrusion to primary users. It is thus not desirable to sense the channel

arbitrarily. In this paper, we are motivated to consider the following problem. A secondary user,

equipped with spectrum sensors, dynamically accesses a channel. If it transmits without/with

colliding with primary users, a certain reward/penalty is obtained. If it senses the channel,

accurate channel information is obtained, but a given channel sensing cost incurs. The third

option for the user is to turn off the sensor/transmitter and go to sleep mode, where no cost/gain

incurs. So when should the secondary user transmit, sense, or sleep, to maximize the total gain?

We derive the optimal transmitting, sensing, and sleeping structure, which is a threshold-based

policy. Our work sheds light on designing sensing and transmitting scheduling protocols for

cognitive radio networks, especially the in-band sensing mechanism in 802.22 networks.

14. DSCA: Dynamic Spectrum Co-Access Between the Primary Users and the

Secondary Users

In the current architecture of dynamic spectrum access, secondary users (SUs) only

opportunistically access the spectrum of primary users (PUs). The resurgence of PUs disrupts

secondary communications, which can result in poor performance for SUs. In this paper, we

propose a novel architecture for dynamic spectrum access, termed dynamic spectrum co-access

(DSCA), to enable the PU and the SU to simultaneously access the licensed spectrum. With

DSCA, SUs transparently incentivize PUs through increasing the PU performance so that SUs

can access the spectrum simultaneously with PUs; hence, there is no disruption to secondary

communications due to the resurgence of PUs. We derive a mathematical model to formulate the

minimum incentives for the spectrum co-access between the PU and the SU and to compute the

region of co-access to determine the SUs that can co-access with a given PU. An algorithm is

also developed to select the co-access primary and secondary links to maximize network

performance. Numerical results indicate that DSCA significantly improves performance

compared with the current architecture of dynamic spectrum access.

15. On Joint Power and Admission Control in Underlay Cellular Cognitive Radio

Networks

We investigate the problem of designing efficient and low-complexity centralized algorithms for

joint power and admission control in a cellular cognitive radio network (CRN) which coexists

with a primary radio network (PRN) in a spectrum underlay fashion. We first derive a simple

one-to-one relation between the signal-to-interference-plus-noise ratio (SINR) vector and its

corresponding power vector of all users of the CRN and PRN, and based on this we propose two

new admission metrics. Then, in an infeasible system, where the minimum acceptable target-

SINRs for all primary and secondary users are not simultaneously reachable, two centralized

algorithms are proposed. These algorithms aim at removing the minimal number of secondary

users (based on the proposed admission metrics), subject to the constraint that all primary users

are supported with their target-SINRs. In an infeasible system, our proposed algorithms

outperform other existing algorithms in terms of complexity and secondary users' outage ratio.

Furthermore, for a feasible system, where all secondary users can be admitted along with all

primary users, by using our derived one-to-one relation between SINR and power vector, we

solve the problems of maximizing aggregate throughput and max-min quality-of-service (QoS)

for secondary users, both subject to the constraint that all primary and secondary users are

supported with their minimum target-SINRs.

16. Cooperative Relay Selection in Cognitive Radio Networks

Cognitive radio has been proposed in recent years to promote the spectrum utilization by

exploiting the existence of spectrum holes. The heterogeneity of both spectrum availability and

traffic demand in secondary users has brought significant challenge for efficient spectrum

allocation in cognitive radio networks. Observing that spectrum resource can be better matched

to traffic demand of secondary users with the help of relay node that has rich spectrum resource,

in this paper we exploit a new research direction for cognitive radio networks by utilizing

cooperative relay to assist the transmission and improve spectrum efficiency. An infrastructure-

based secondary network architecture has been proposed to leverage relay-assisted discontiguous

OFDM (D-OFDM) for data transmission. In this architecture, relay node will be selected which

can bridge the source and the destination using its common channels between those two nodes.

With the introduction of cooperative relay, many unique problems should be considered,

especially the issue for relay selection and spectrum allocation. We propose a centralized

heuristic solution to address the new resource allocation problem. To demonstrate the feasibility

and performance of cooperative relay for cognitive radio, a new MAC protocol has been

proposed and implemented in a Universal Software Radio Peripheral (USRP)-based testbed.

Experimental results show that the throughput of the whole system is greatly increased by

exploiting the benefit of cooperative relay.

17. Statistical Modeling of Spectrum Sensing Energy in Multi-Hop Cognitive Radio

Networks

The aim of this letter is to address the statistical modeling of the spectrum sensing energy

consumption in cognitive radio networks. A Poisson point process has been shown to yield

tractable and accurate results for the modeling of the interference in cognitive radio networks.

We adopt this homogeneous stochastic process to develop an unified framework for deriving the

energy consumption of the spectrum sensing in clustered cognitive radio networks. Furthermore,

we extend the framework to multi-hop networks. The letter demonstrates that the spectrum

sensing energy can be modeled as a Gamma-truncated distribution, as a function of the number

of secondary users, their spatial density, and the number of hops of the cognitive radio network.

18. Adaptive Random Access for Cooperative Spectrum Sensing in Cognitive Radio

Networks

In this paper, an adaptive cooperative spectrum sensing scheme using random access is proposed

in a cognitive radio network. Although cooperative spectrum sensing improves the performance

of spectrum sensing considerably, the problem of how to collect sensing data should be solved

for the implementation of the cooperative sensing. This is not an easy problem because

complicated coordination between secondary users paprticipating in the cooperative sensing is

required. This study addresses this problem in an environment of unequal SNR values of primary

user signal at the secondary users. In the proposed scheme, random access is used to collect the

spectrum sensing data of the secondary users during collection period and the length of the

collection period is determined adaptively based on the sensing data collected so far. Thus,

complex slot management for the collection of the sensing data is not necessary. This adaptive

determination of the collection period is formulated as a finite-horizon decision problem.

Backward induction approach is employed to decide the optimal stopping time of the collection

period. In addition, a heuristic algorithm is proposed, which almost equals the performance of

the backward induction method and whose time complexity is much smaller than the backward

induction scheme. Analysis of the proposed scheme is also provided. Numerical results show

that the proposed scheme performs much better than other conventional methods.

19. Robust Power Control Under Location and Channel Uncertainty in Cognitive Radio

Networks

In this letter, we consider the power control problem in cognitive radio (CR) networks when both

primary user (PU) location and wireless channel are unknown. Prior work in power control

assumes perfect knowledge of PU and CR locations, which is not practical due to localization

errors and node mobility. We assume the distance estimation error in CR-PU links to model

location uncertainties and derive the distribution of channel gain with distance-dependent path

loss and shadowing. We then proceed to develop an optimization framework for CR power

control, which maximizes the CR data rate under PU interference power constraint. Simulation

results showing the CR data rate and interference probability to the PUs are presented to

demonstrate the superior performance of the proposed algorithm compared with reference

schemes.

20. Energy Efficient Collaborative Spectrum Sensing Based on Trust Management in

Cognitive Radio Networks

An energy efficient collaborative spectrum sensing (EE-CSS) protocol, based on trust

management, is proposed. The protocol achieves energy efficiency by reducing the total number

of sensing reports exchanged between the honest secondary users (HSUs) and the secondary user

base station (SUBS) in a traditional collaborative spectrum sensing (T-CSS) protocol. It is shown

that the minimum total number of sensing reports required to satisfy a target global false alarm

(FA) and missed detection (MD) probabilities in T-CSS is higher than that in EE-CSS.

Expressions for the steady-state average SU trust value τ̅H and total number NH of SU sensing

reports transmitted are derived, as is an expression for the energy consumption, in EE-CSS and

T-CSS. The global FA and detection probabilities Qf and Qd are obtained for a commonly used

decision fusion technique. The impact of link outages on τ̅H, NH , Qf, and Qd is also analyzed. The

results show that the energy consumption in EE-CSS can be much lower compared to that in T-

CSS for long range communications where the transmit energy is dominant.

21. Improving the Network Lifetime of MANETs through Cooperative MAC Protocol

Design

Cooperative communication, which utilizes nearby terminals to relay the overhearing

information to achieve the diversity gains, has a great potential to improve the transmitting

efficiency in wireless networks. To deal with the complicated medium access interactions

induced by relaying and leverage the benefits of such cooperation, an efficient Cooperative

Medium Access Control (CMAC) protocol is needed. In this paper, we propose a novel cross-

layer Distributed Energy-adaptive Location-based CMAC protocol, namely DEL-CMAC, for

Mobile Ad-hoc NETworks (MANETs). The design objective of DEL-CMAC is to improve the

performance of the MANETs in terms of network lifetime and energy efficiency. A practical

energy consumption model is utilized in this paper, which takes the energy consumption on both

transceiver circuitry and transmit amplifier into account. A distributed utility-based best relay

selection strategy is incorporated, which selects the best relay based on location information and

residual energy. Furthermore, with the purpose of enhancing the spatial reuse, an innovative

network allocation vector setting is provided to deal with the varying transmitting power of the

source and relay terminals. We show that the proposed DEL-CMAC significantly prolongs the

network lifetime under various circumstances even for high circuitry energy consumption cases

by comprehensive simulation study.

22. Defending Against Collaborative Attacks by Malicious Nodes in MANETs: A

Cooperative Bait Detection Approach

In mobile ad hoc networks (MANETs), a primary requirement for the establishment of

communication among nodes is that nodes should cooperate with each other. In the presence of

malevolent nodes, this requirement may lead to serious security concerns; for instance, such

nodes may disrupt the routing process. In this context, preventing or detecting malicious nodes

launching grayhole or collaborative blackhole attacks is a challenge. This paper attempts to

resolve this issue by designing a dynamic source routing (DSR)-based routing mechanism, which

is referred to as the cooperative bait detection scheme (CBDS), that integrates the advantages of

both proactive and reactive defense architectures. Our CBDS method implements a reverse

tracing technique to help in achieving the stated goal. Simulation results are provided, showing

that in the presence of malicious-node attacks, the CBDS outperforms the DSR, 2ACK, and best-

effort fault-tolerant routing (BFTR) protocols (chosen as benchmarks) in terms of packet

delivery ratio and routing overhead (chosen as performance metrics).

23. Joint Optimal Data Rate and Power Allocation in Lossy Mobile Ad Hoc Networks

with Delay-Constrained Traffics So

The emerging wireless energy transfer technology enables charging sensor batteries in a wireless

sensor network (WSN) and maintaining perpetual operation of the network. Recent breakthrough

in this area has opened up a new dimension to the design of sensor network protocols. In the

meanwhile, mobile data gathering has been considered as an efficient alternative to data relaying

in WSNs. However, time variation of recharging rates in wireless rechargeable sensor networks

imposes a great challenge in obtaining an optimal data gathering strategy. In this paper, we

propose a framework of joint wireless energy replenishment and anchor-point based mobile data

gathering (WerMDG) in WSNs by considering various sources of energy consumption and time-

varying nature of energy replenishment. To that end, we first determine the anchor point

selection strategy and the sequence to visit the anchor points. We then formulate the WerMDG

problem into a network utility maximization problem which is constrained by flow, energy

balance, link and battery capacity and the bounded sojourn time of the mobile collector.

Furthermore, we present a distributed algorithm composed of cross-layer data control,

scheduling and routing subalgorithms for each sensor node, and sojourn time allocation

subalgorithm for the mobile collector at different anchor points. We also provide the

convergence analysis of these subalgorithms. Finally, we implement the WerMDG algorithm in a

distributed manner in the NS-2 simulator and give extensive numerical results to verify the

convergence of the proposed algorithm and the impact of utility weight, link capacity and

recharging rate on network performance.

24. Mobile-Projected Trajectory Algorithm With Velocity-Change Detection for

Predicting Residual Link Lifetime in MANET

We study the estimation of residual link lifetime (RLL) in mobile ad hoc networks (MANETs)

using the distances between the link's nodes. We first prove that to compute uniquely the RLL, at

least four distance measurements are required. We also demonstrate that random measurement

errors are the dominant factor in prediction inaccuracy and that systematic errors are negligible.

We then propose a mobile-projected trajectory (MPT) algorithm, which estimates the relative

trajectory between two nodes from periodical measurements of the distances between them.

Using the relative trajectory, the algorithm estimates the RLL of the link between the two nodes.

For comparison purposes, we derive a theoretical upper bound on the achievable prediction

inaccuracy by any distance-based RLL prediction algorithm with unknown but finitely bounded

measurement-error distribution. To account for velocity changes, the MPT is enhanced with a

velocity-change detection (VCD) test. Performance evaluation demonstrates robustness in RLL

prediction for piecewise-linear trajectory and multiple velocity changes during the link lifetime.

25. BRACER: A Distributed Broadcast Protocol in Multi-Hop Cognitive Radio Ad Hoc

Networks with Collision Avoidance

Broadcast is an important operation in wireless ad hoc networks where control information is

usually propagated as broadcasts for the realization of most networking protocols. In traditional

ad hoc networks, since the spectrum availability is uniform, broadcasts are delivered via a

common channel which can be heard by all users in a network. However, in cognitive radio (CR)

ad hoc networks, different unlicensed users may acquire different available channel sets. This

non-uniform spectrum availability imposes special design challenges for broadcasting in CR ad

hoc networks. In this paper, a fully-distributed Broadcast protocol in multi-hop Cognitive Radio

ad hoc networks with collision avoidance, BRACER, is proposed. In our design, we consider

practical scenarios that each unlicensed user is not assumed to be aware of the global network

topology, the spectrum availability information of other users, and time synchronization

information. By intelligently downsizing the original available channel set and designing the

broadcasting sequences and scheduling schemes, our proposed broadcast protocol can provide

very high successful broadcast ratio while achieving very short average broadcast delay. It can

also avoid broadcast collisions. To the best of our knowledge, this is the first work that addresses

the unique broadcasting challenges in multi-hop CR ad hoc networks with collision avoidance.

26. Interference-Based Topology Control Algorithm for Delay-Constrained Mobile Ad

Hoc Networks

As the foundation of routing, topology control should minimize the interference among nodes,

and increase the network capacity. With the development of mobile ad hoc networks (MANETs),

there is a growing requirement of quality of service (QoS) in terms of delay. In order to meet the

delay requirement, it is important to consider topology control in delay constrained environment,

which is contradictory to the objective of minimizing interference. In this paper, we focus on the

delay-constrained topology control problem, and take into account delay and interference jointly.

We propose a cross-layer distributed algorithm called interference-based topology control

algorithm for delay-constrained (ITCD) MANETs with considering both the interference

constraint and the delay constraint, which is different from the previous work. The transmission

delay, contention delay and the queuing delay are taken into account in the proposed algorithm.

Moreover, the impact of node mobility on the interference-based topology control algorithm is

investigated and the unstable links are removed from the topology. The simulation results show

that ITCD can reduce the delay and improve the performance effectively in delay-constrained

mobile ad hoc networks.

27. Cooperative Load Balancing and Dynamic Channel Allocation for Cluster-Based

Mobile Ad Hoc Networks

Mobile ad hoc networks (MANETs) are becoming increasingly common, and typical network

loads considered for MANETs are increasing as applications evolve. This, in turn, increases the

importance of bandwidth efficiency while maintaining tight requirements on energy

consumption, delay and jitter. Coordinated channel access protocols have been shown to be well

suited for highly loaded MANETs under uniform load distributions. However, these protocols

are in general not as well suited for non-uniform load distributions as uncoordinated channel

access protocols due to the lack of on-demand dynamic channel allocation mechanisms that exist

in infrastructure based coordinated protocols. In this paper, we present a lightweight dynamic

channel allocation mechanism and a cooperative load balancing strategy that are applicable to

cluster based MANETs to address this problem. We present protocols that utilize these

mechanisms to improve performance in terms of throughput, energy consumption and inter-

packet delay variation (IPDV). Through extensive simulations we show that both dynamic

channel allocation and cooperative load balancing improve the bandwidth efficiency under non-

uniform load distributions compared to protocols that do not use these mechanisms as well as

compared to the IEEE 802.15.4 protocol with GTS mechanism and the IEEE 802.11

uncoordinated protocol.

28. CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes

Mobile ad-hoc networks (MANETs) assume that mobile nodes voluntary cooperate in order to

work properly. This cooperation is a cost-intensive activity and some nodes can refuse to

cooperate, leading to a selfish node behaviour. Thus, the overall network performance could be

seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes.

However, the detection process performed by watchdogs can fail, generating false positives and

false negatives that can induce to wrong operations. Moreover, relying on local watchdogs alone

can lead to poor performance when detecting selfish nodes, in term of precision and speed. This

is specially important on networks with sporadic contacts, such as delay tolerant networks

(DTNs), where sometimes watchdogs lack of enough time or information to detect the selfish

nodes. Thus, we propose collaborative contact-based watchdog (CoCoWa) as a collaborative

approach based on the diffusion of local selfish nodes awareness when a contact occurs, so that

information about selfish nodes is quickly propagated. As shown in the paper, this collaborative

approach reduces the time and increases the precision when detecting selfish nodes.

29. Estimating the Available Medium Access Bandwidth of IEEE 802.11 Ad Hoc

Networks with Concurrent Transmissions

Concurrent transmission scheduling mechanisms can significantly improve the total throughput

of IEEE 802.11 ad hoc networks. What remains unaddressed, however, is how to estimate the

available medium access bandwidth (AB) of a link under concurrent transmission scenarios, i.e.,

the maximum throughput that can be obtained without violating the quality-of-service (QoS)

requirements of the existing flows. In this paper, we focus on estimating the available medium

AB of IEEE 802.11 ad hoc networks with the control-gap-based concurrent transmissions. We

first introduce the upper bound of the AB of a link, and then, we present an algorithm to estimate

the available transmission/reception duration of the node by a distributed manner. We further

derive a preliminary estimation of the AB by analyzing the nonoverlap between the medium

availability of the sender and recipient of a link. Finally, we refine the estimation by taking into

account the transmission failures induced by hidden nodes and concurrent collisions. Extensive

simulations demonstrate the accuracy of the proposed approach.

30. Dynamic Channel Assignment for Wireless Sensor Networks: A Regret Matching

Based Approach

Multiple channels in Wireless Sensor Networks (WSNs) are often exploited to support parallel

transmission and to reduce interference. However, the extra overhead posed by the multi-channel

usage coordination dramatically challenges the energy-constrained WSNs. In this paper, we

propose a Regret Matching based Channel Assignment algorithm (RMCA) to address this

challenge, in which each sensor node updates its choice of channels according to the historical

record of these channels' performance to reduce interference. The advantage of RMCA is that it

is highly distributed and requires very limited information exchange among sensor nodes. It is

proved that RMCA converges almost surely to the set of correlated equilibrium. Moreover,

RMCA can adapt the channel assignment among sensor nodes to the time-variant flows and

network topology. Simulations show that RMCA achieves better network performance in terms

of both delivery ratio and packet latency than CONTROL [1], MMSN [2] and randomized

CSMA. In addition, real hardware experiments are conducted to demonstrate that RMCA is easy

to be implemented and performs better.

31. Segment-Based Anomaly Detection with Approximated Sample Covariance Matrix

in Wireless Sensor Networks

In wireless sensor networks (WSNs), it has been observed that most abnormal events persist over

a considerable period of time instead of being transient. As existing anomaly detection

techniques usually operate in a point-based manner that handles each observation individually,

they are unable to reliably and efficiently report such long-term anomalies appeared in an

individual sensor node. Therefore, in this paper, we focus on a new technique for handling data

in a segment-based manner. Considering a collection of neighbouring data segments as random

variables, we determine those behaving abnormally by exploiting their spatial predictabilities

and, motivated by spatial analysis, specifically investigate how to implement a prediction

variance detector in a WSN. As the communication cost incurred in aggregating a covariance

matrix is finally optimised using the Spearman's rank correlation coefficient and differential

compression, the proposed scheme is able to efficiently detect a wide range of long-term

anomalies. In theory, comparing to the regular centralised approach, it can reduce the

communication cost by approximately 80 percent. Moreover, its effectiveness is demonstrated by

the numerical experiments, with a real world data set collected by the Intel Berkeley Research

Lab (IBRL).

32. Maximum Lifetime Scheduling for Target Coverage and Data Collection in Wireless

Sensor Networks

Target coverage and data collection are two fundamental problems for wireless sensor networks

(WSNs). Target coverage is needed to select sensors in a given area that can monitor a set of

interesting points. Data collection is needed to transmit the sensed data from sensors to a sink.

Since, in many applications, sensors are battery powered, it is expected that a WSN can work

untended for a long period. This paper addresses the scheduling problems for both target

coverage and data collection in WSNs with the objective of maximizing network lifetime. First, a

polynomial-time approximation scheme is developed for the case where the density of target

points is bounded, and then, a polynomial-time constant-factor approximation algorithm is

developed for the general case. It is also proved that it is NP-hard to find a maximum lifetime

scheduling of target cover and data collection for a WSN, even if all the sensors have the same

sensing radius and the same transmission radius. Further, the practical efficiency of our

algorithms is analyzed through simulation. These extensive simulation results show better

performances of our algorithms compared with other research findings.

33. Mobile Data Gathering with Load Balanced Clustering and Dual Data Uploading in

Wireless Sensor Networks

In this paper, a three-layer framework is proposed for mobile data collection in wireless sensor

networks, which includes the sensor layer, cluster head layer, and mobile collector (called

SenCar) layer. The framework employs distributed load balanced clustering and dual data

uploading, which is referred to as LBC-DDU. The objective is to achieve good scalability, long

network lifetime and low data collection latency. At the sensor layer, a distributed load balanced

clustering (LBC) algorithm is proposed for sensors to self-organize themselves into clusters. In

contrast to existing clustering methods, our scheme generates multiple cluster heads in each

cluster to balance the work load and facilitate dual data uploading. At the cluster head layer, the

inter-cluster transmission range is carefully chosen to guarantee the connectivity among the

clusters. Multiple cluster heads within a cluster cooperate with each other to perform energy-

saving inter-cluster communications. Through inter-cluster transmissions, cluster head

information is forwarded to SenCar for its moving trajectory planning. At the mobile collector

layer, SenCar is equipped with two antennas, which enables two cluster heads to simultaneously

upload data to SenCar in each time by utilizing multi-user multiple-input and multiple-output

(MU-MIMO) technique. The trajectory planning for SenCar is optimized to fully utilize dual

data uploading capability by properly selecting polling points in each cluster. By visiting each

selected polling point, SenCar can efficiently gather data from cluster heads and transport the

data to the static data sink. Extensive simulations are conducted to evaluate the effectiveness of

the proposed LBC-DDU scheme. The results show that when each cluster has at most two cluster

heads, LBC-DDU achieves over 50 percent energy saving per node and 60 percent energy saving

on cluster heads comparing with data collection through multi-hop relay to the static data sink,

and 20 percent - horter data collection time compared to traditional mobile data gathering.

34. Joint Cooperative Routing and Power Allocation for Collision Minimization in

Wireless Sensor Networks With Multiple Flows

In this letter, a cross-layer cooperative routing algorithm is proposed for minimizing the collision

probability subject to an end-to-end outage probability constraint. We develop a collision

minimization algorithm by combining cooperative transmission, optimal power allocation, and

route selection. The proposed cooperative routing algorithm, called minimum collision

cooperative routing (MCCR), selects the route that causes minimum collision probability to other

nodes in the network. Results show that MCCR can significantly reduce the collision probability

compared with existing cooperative routing schemes.

35. PWDGR: Pair-Wise Directional Geographical Routing Based on Wireless Sensor

Network

Multipath routing in wireless multimedia sensor network makes it possible to transfer data

simultaneously so as to reduce delay and congestion and it is worth researching. However, the

current multipath routing strategy may cause problem that the node energy near sink becomes

obviously higher than other nodes which makes the network invalid and dead. It also has serious

impact on the performance of wireless multimedia sensor network (WMSN). In this paper, we

propose a pair-wise directional geographical routing (PWDGR) strategy to solve the energy

bottleneck problem. First, the source node can send the data to the pair-wise node around the

sink node in accordance with certain algorithm and then it will send the data to the sink node.

These pair-wise nodes are equally selected in 360° scope around sink according to a certain

algorithm. Therefore, it can effectively relieve the serious energy burden around Sink and also

make a balance between energy consumption and end-to-end delay. Theoretical analysis and a

lot of simulation experiments on PWDGR have been done and the results indicate that PWDGR

is superior to the proposed strategies of the similar strategies both in the view of the theory and

the results of those simulation experiments. With respect to the strategies of the same kind,

PWDGR is able to prolong 70% network life. The delay time is also measured and it is only

increased by 8.1% compared with the similar strategies.

36. A Spectral Clustering Approach to Identifying Cuts in Wireless Sensor Networks

Wireless sensor networks (WSNs) often suffer from the disrupted connectivity due to

unpredictable wireless channels, early depletion of node energy, and physical tampering by

hostile users. The existence of a disconnected segment of the network referred to as network cut,

leads to data loss, wasted power consumption, and congestion in the WSN. However, existing

approaches to network cut detection in the WSN rely on the assumption that a node or a link

either works normally or fails, without considering the uncertain and random features of wireless

links in the WSN. In this paper, we extend the notion of the network cut based on the realistic

wireless channel model. Furthermore, we formulate the problem of minimizing the normalized

cut (Ncut) with critical nodes, considering the quality of wireless links, degree weights, and

different priorities of sensor nodes. Then, we propose a network cut identification algorithm and

dominant eigenvector computation algorithm that efficiently identify multiple network cuts by

computing multiple eigenvalues and eigenvectors according to a given parameter of eigenvalue

gap. Extensive simulations are conducted to examine the effectiveness and robustness of the

proposed approach. The results show that the proposed method strikes a balance between

minimizing the Ncut objective and the degree of disconnection of critical nodes and achieves a

better performance than existing algorithms.

37. Non cooperative Game-Based Energy Welfare Topology Control for Wireless

Sensor Networks

In this paper, we address the problem of minimizing energy consumption and balancing energy

in a wireless sensor network, using a topology control algorithm. Such an algorithm is able to

minimize and balance energy consumption by reasonably tuning the transmission power level

while preserving network connectivity. This paper proposes an energy welfare topology control

using game theory approach, which adopts the welfare function from social sciences to compute

energy welfare as a goodness measure for energy populations. When each node tries to maximize

the energy welfare of its local society, it collectively leads to energy balancing. We show that the

resulting game is a potential game and that it possesses a unique Nash equilibrium, which is

Pareto optimal. To evaluate the performance of the proposed algorithm, extensive simulations

were carried out, and the results were compared with the existing algorithm. The results

demonstrated the superiority of the proposed algorithm over the existing algorithm.

38. Opportunistic Routing Algorithm for Relay Node Selection in Wireless Sensor

Networks

Energy savings optimization becomes one of the major concerns in the wireless sensor network

(WSN) routing protocol design, due to the fact that most sensor nodes are equipped with the

limited nonrechargeable battery power. In this paper, we focus on minimizing energy

consumption and maximizing network lifetime for data relay in one-dimensional (1-D) queue

network. Following the principle of opportunistic routing theory, multihop relay decision to

optimize the network energy efficiency is made based on the differences among sensor nodes, in

terms of both their distance to sink and the residual energy of each other. Specifically, an Energy

Saving via Opportunistic Routing (ENS_OR) algorithm is designed to ensure minimum power

cost during data relay and protect the nodes with relatively low residual energy. Extensive

simulations and real testbed results show that the proposed solution ENS_OR can significantly

improve the network performance on energy saving and wireless connectivity in comparison

with other existing WSN routing schemes.

39. An Efficient Cluster-Tree Based Data Collection Scheme for Large Mobile Wireless

Sensor Networks

Amidst of the growing impact of wireless sensor networks (WSNs) on real world applications,

numerous schemes have been proposed for collecting data on multipath routing, tree, clustering,

and cluster tree. Effectiveness of WSNs only depends on the data collection schemes. Existing

methods cannot provide a guaranteed reliable network about mobility, traffic, and end-to-end

connection, respectively. To mitigate such kind of problems, a simple and effective scheme is

proposed, which is named as cluster independent data collection tree (CIDT). After the cluster

head election and cluster formation, CIDT constructs a data collection tree (DCT) based on the

cluster head location. In DCT, data collection node (DCN) does not participate in sensing, which

is simply collecting the data packet from the cluster head and delivering it into sink. CIDT

minimizes the energy exploitation, end-to-end delay and traffic of cluster head due to transfer of

data with DCT. CIDT provides less complexity involved in creating a tree structure, which

maintains the energy consumption of cluster head that helps to reduce the frequent cluster

formation and maintain a cluster for considerable amount of time. The simulation results show

that CIDT provides better QoS in terms of energy consumption, throughput, end-to-end delay,

and network lifetime for mobility-based WSNs.

40. Energy Efficient Clustering Scheme for Prolonging the Lifetime of Wireless Sensor

Network With Isolated Nodes

A suitable clustering algorithm for grouping sensor nodes can increase the energy efficiency of

WSNs. However, clustering requires additional overhead, such as cluster head selection and

assignment, and cluster construction. This paper proposes a new regional energy aware

clustering method using isolated nodes for WSNs, called Regional Energy Aware Clustering

with Isolated Nodes (REAC-IN). In REAC-IN, CHs are selected based on weight. Weight is

determined according to the residual energy of each sensor and the regional average energy of all

sensors in each cluster. Improperly designed distributed clustering algorithms can cause nodes to

become isolated from CHs. Such isolated nodes communicate with the sink by consuming excess

amount of energy. To prolong network lifetime, the regional average energy and the distance

between sensors and the sink are used to determine whether the isolated node sends its data to a

CH node in the previous round or to the sink. The simulation results of the current study revealed

that REAC-IN outperforms other clustering algorithms.

41. Lightweight Self-Adapting Linear Prediction Algorithms for Wireless Sensor Networks

In wireless sensor networks, data prediction is an efficient technique to reduce the number of

redundant data transmissions for applications that require sensor nodes to regularly report their

readings. This paper proposes a series of novel self-adapting linear prediction algorithms for the

sensor nodes to report their readings to the sink or to the cluster head when clustering technology

is used. We propose a dynamical extraction algorithm to select a suitable training set from the

history time series data; we propose an information criterion-based searching algorithm to find a

better training set if the chosen training set is not valid for the training of the new predictors; and

we propose an exception detection scheme to determine whether the linear predictors are

efficient for data prediction. Experimental results based on the practical temperature time series

data demonstrate the efficiency of the proposed algorithms, and our prediction algorithms show a

significant improvement of the performance in reducing the number of data transmissions and

the transmission energy cost.

42. Energy Management and Cross Layer Optimization for Wireless Sensor Network Powered by Heterogeneous Energy Sources

Recently, utilizing renewable energy for wireless system has attracted extensive attention.

However, due to the instable energy supply and the limited battery capacity, renewable energy

cannot guarantee to provide the perpetual operation for wireless sensor networks (WSN). The

coexistence of renewable energy and electricity grid is expected as a promising energy supply

manner to remain function for a potentially infinite lifetime. In this paper, we propose a new

system model suitable for WSN, taking into account multiple energy consumptions due to

sensing, transmission and reception, heterogeneous energy supplies from renewable energy,

electricity grid and mixed energy, and multidimension stochastic natures due to energy

harvesting profile, electricity price and channel condition. A discrete-time stochastic cross-layer

optimization problem is formulated to achieve the optimal trade-off between the time-average

rate utility and electricity cost subject to the data and energy queuing stability constraints. The

Lyapunov drift-plus-penalty with perturbation technique and block coordinate descent method is

applied to obtain a fully distributed and low-complexity cross-layer algorithm only requiring

knowledge of the instantaneous system state. The explicit trade-off between the optimization

objective and queue backlog is theoretically proven. Finally, the extensive simulations verify the

theoretic claims.

43. A Secure Scheme Against Power Exhausting Attacks in Hierarchical Wireless Sensor Networks

Security and energy efficiency are critical concerns in wireless sensor network (WSN) design.

This paper aims to develop an energy-efficient secure scheme against power exhausting attacks,

especially the denial-of-sleep attacks, which can shorten the lifetime of WSNs rapidly. Although

various media access control (MAC) protocols have been proposed to save the power and extend

the lifetime of WSNs, the existing designs of MAC protocol are insufficient to protect the WSNs

from denial-of-sleep attacks in MAC layer. This is attributed to the fact that the well-known

security mechanisms usually awake the sensor nodes before these nodes are allowed to execute

the security processes. Therefore, the practical design is to simplify the authenticating process in

order to reduce the energy consumption of sensor nodes and enhance the performance of the

MAC protocol in countering the power exhausting attacks. This paper proposes a cross-layer

design of secure scheme integrating the MAC protocol. The analyses show that the proposed

scheme can counter the replay attack and forge attack in an energy-efficient way. The detailed

analysis of energy distribution shows a reasonable decision rule of coordination between energy

conservation and security requirements for WSNs.

44. ACPN: A Novel Authentication Framework with Conditional Privacy-Preservation and Non-Repudiation for VANETs 

In Vehicular Ad hoc NETworks (VANETs), authentication is a crucial security service for both

inter-vehicle and vehicle-roadside communications. On the other hand, vehicles have to be

protected from the misuse of their private data and the attacks on their privacy, as well as to be

capable of being investigated for accidents or liabilities from non-repudiation. In this paper, we

investigate the authentication issues with privacy preservation and non-repudiation in VANETs.

We propose a novel framework with preservation and repudiation (ACPN) for VANETs. In

ACPN, we introduce the public-key cryptography (PKC) to the pseudonym generation, which

ensures legitimate third parties to achieve the non-repudiation of vehicles by obtaining vehicles'

real IDs. The self-generated PKCbased pseudonyms are also used as identifiers instead of vehicle

IDs for the privacy-preserving authentication, while the update of the pseudonyms depends on

vehicular demands. The existing ID-based signature (IBS) scheme and the ID-based

online/offline signature (IBOOS) scheme are used, for the authentication between the road side

units (RSUs) and vehicles, and the authentication among vehicles, respectively. Authentication,

privacy preservation, non-repudiation and other objectives of ACPN have been analyzed for

VANETs. Typical performance evaluation has been conducted using efficient IBS and IBOOS

schemes. We show that the proposed ACPN is feasible and adequate to be used efficiently in the

VANET environment.

45. Energy-Efficient Scheduling in Green Vehicular Infrastructure With Multiple Roadside Units

In this paper, we propose low-complexity algorithms for downlink traffic scheduling in green

vehicular roadside infrastructure. In multiple roadside unit (RSU) deployments, the energy

provisioning of the RSUs may differ, and it is therefore desirable to balance RSU usage from a

normalized min-max energy viewpoint. This paper considers both splittable RSU assignment

(SRA) and unsplittable RSU asssignment (URA) scheduling. An offline integer linear

programming bound is first derived for normalized min-max RSU energy usage. We then show

that in the SRA case, there is a polynomial complexity 2-approximation bound for the

normalized min-max energy schedule. This paper then proposes several online scheduling

algorithms. The first is a greedy online algorithm that makes simple RSU selections, followed by

minimum-energy time slot assignments. A normalized min-max algorithm is then proposed [2-

approximation online algorithm (TOAA)], which is an online version of the 2-approximation

bound. Two algorithms are then introduced based on a potential function scheduling approach.

The 1-objective algorithm uses an objective based on normalized min-max energy, and we show

that it has an upper bounded worst-case competitive ratio performance. The 2-objective

algorithm uses the same approach but incorporates a total-energy secondary objective as well.

Results from a variety of experiments show that the proposed scheduling algorithms perform

well. In particular, we find that in the SRA case, the TOAA algorithm performs very close to the

lower bound but at the expense of having to reassign time slots whenever a new vehicle arrives.

In the URA case, our low-complexity 1-objective algorithm performs better than the others over

a wide range of traffic conditions.

46. Delay-Constrained Data Aggregation in VANETs

Data aggregation has been recognized as an effective technique for reducing communication

costs while obtaining useful aggregated information. In this paper, we study the crucial problem

of delay-constrained data aggregation in vehicular ad hoc networks (VANETs), which has not

been well studied in the literature. With the analysis based on real traces, we observe that there is

heterogeneity with node contact patterns, which indicates that some nodes contact other nodes

more frequently. Motivated by this observation, we propose an approach called aTree. The

centralized aTree first constructs a data aggregation tree based on the shortest path tree and then

assigns a waiting time budget to each node on the tree based on dynamic programming. We

further develop a distributed aTree, in which a shortest path tree is built in a distributed fashion,

and nodes determine their waiting time budgets collaboratively. We have performed extensive

simulations on real taxi traces, and results show that our aTree schemes incur much lower

transmission overhead while achieving the same performance compared with other schemes.

47. An Evolutionary Game Theory-Based Approach to Cooperation in VANETs Under Different Network Conditions

Vehicular Ad hoc NETworks (VANETs) belong to a class of complex networks due to constant

addition and deletion of nodes. Stimulating cooperation in these networks is a research challenge

due to this uncertainty. The reason is that the node behavior is highly influenced by the

neighborhood structure. Game theory has been significantly used to model ad hoc networks and

optimize cooperation. However, in vehicular interactions, apart from the individual node

behavior, networking properties play a vital role in the evolution of cooperation. This paper

presents a public goods game (PGG) group interaction model for vehicular networks. We

analyze how networking properties can impact the diffusion of cooperation. Simulation results

show that higher network connectivity induces higher clustering in the network. This influences

the probability of nodes receiving common packets from the neighborhood. The average path

length proportional to clustering impacts the benefit sharing in the neighborhood. Results show

that cooperation diffusion in these networks cannot be forced but evolves with different

networking conditions

48. Speed Adaptive Probabilistic Flooding for Vehicular Ad Hoc Networks

A significant issue in vehicular ad hoc networks is the design of an effective broadcast scheme

which can facilitate the fast and reliable dissemination of emergency warning messages in the

vicinity of an expected event, such as a car accident. In this work we propose a novel solution to

this problem, which we refer to as Speed Adaptive Probabilistic Flooding. The scheme employs

probabilistic flooding to mitigate the effects of the broadcast storm problem, typical when using

blind flooding, and its unique feature is that the rebroadcast probability is regulated adaptively

based on the vehicle speed to account for varying traffic densities within the transportation

network. The protocol enjoys a number of benefits relative to other approaches: it is simple to

implement, it does not introduce additional communication burden, as it relies on local

information only and it does not rely on the existence of a positioning system which may not

always be available. The scheme is evaluated on different sections of the highway system in the

City of Los Angeles using an integrated platform combining the OPNET Modeler and the

VISSIM simulator. Simulation results indicate that the proposed scheme fulfills its design

objectives as it achieves high reachability and low latency of message delivery in a number of

scenarios. Its robustness with respect to changing number of hops and transmission ranges is also

demonstrated.

49. A Novel Centralized TDMA-Based Scheduling Protocol for Vehicular Networks

In this paper, we propose a novel centralized time-division multiple access (TDMA)-based

scheduling protocol for practical vehicular networks based on a new weight-factor-based

scheduler. A roadside unit (RSU), as a centralized controller, collects the channel state

information and the individual information of the communication links within its communication

coverage, and it calculates their respective scheduling weight factors, based on which scheduling

decisions are made by the RSU. Our proposed scheduling weight factor mainly consists of three

parts, i.e., the channel quality factor, the speed factor, and the access category factor. In addition,

a resource-reusing mode among multiple vehicle-to-vehicle (V2V) links is permitted if the

distances between every two central vehicles of these V2V links are larger than a predefined

interference interval. Compared with the existing medium-access-control protocols in vehicular

networks, the proposed centralized TDMA-based scheduling protocol can significantly improve

the network throughput and can be easily incorporated into practical vehicular networks.

50. An Efficient Cluster-Tree Based Data Collection Scheme for Large Mobile Wireless Sensor Networks

Amidst of the growing impact of wireless sensor networks (WSNs) on real world applications,

numerous schemes have been proposed for collecting data on multipath routing, tree, clustering,

and cluster tree. Effectiveness of WSNs only depends on the data collection schemes. Existing

methods cannot provide a guaranteed reliable network about mobility, traffic, and end-to-end

connection, respectively. To mitigate such kind of problems, a simple and effective scheme is

proposed, which is named as cluster independent data collection tree (CIDT). After the cluster

head election and cluster formation, CIDT constructs a data collection tree (DCT) based on the

cluster head location. In DCT, data collection node (DCN) does not participate in sensing, which

is simply collecting the data packet from the cluster head and delivering it into sink. CIDT

minimizes the energy exploitation, end-to-end delay and traffic of cluster head due to transfer of

data with DCT. CIDT provides less complexity involved in creating a tree structure, which

maintains the energy consumption of cluster head that helps to reduce the frequent cluster

formation and maintain a cluster for considerable amount of time. The simulation results show

that CIDT provides better QoS in terms of energy consumption, throughput, end-to-end delay,

and network lifetime for mobility-based WSNs.

51. Multi-Node Wireless Energy Charging in Sensor Networks

Wireless energy transfer based on magnetic resonant coupling is a promising technology to

replenish energy to a wireless sensor network (WSN). However, charging sensor nodes one at a

time poses a serious scalability problem. Recent advances in magnetic resonant coupling show

that multiple nodes can be charged at the same time. In this paper, we exploit this multi-node

wireless energy transfer technology and investigate whether it is a scalable technology to address

energy issues in a WSN. We consider a wireless charging vehicle (WCV) periodically traveling

inside a WSN and charging sensor nodes wirelessly. Based on charging range of the WCV, we

propose a cellular structure that partitions the two-dimensional plane into adjacent hexagonal

cells. We pursue a formal optimization framework by jointly optimizing traveling path, flow

routing, and charging time. By employing discretization and a novel Reformulation-

Linearization Technique (RLT), we develop a provably near-optimal solution for any desired

level of accuracy. Through numerical results, we demonstrate that our solution can indeed

address the charging scalability problem in a WSN.

52. Analysis of a “/0” Stealth Scan From a Botnet

Botnets are the most common vehicle of cyber-criminal activity. They are used for spamming,

phishing, denial of service attacks, brute-force cracking, stealing private information, and cyber

warfare. Botnets carry out network scans for several reasons, including searching for vulnerable

machines to infect and recruit into the botnet, probing networks for enumeration or penetration,

etc. We present the measurement and analysis of a horizontal scan of the entire IPv4 address

space conducted by the Sality botnet in February of last year. This 12-day scan originated from

approximately 3 million distinct IP addresses, and used a heavily coordinated and unusually

covert scanning strategy to try to discover and compromise VoIP-related (SIP server)

infrastructure. We observed this event through the UCSD Network Telescope, a /8 darknet

continuously receiving large amounts of unsolicited traffic, and we correlate this traffic data with

other public sources of data to validate our inferences. Sality is one of the largest botnets ever

identified by researchers, its behavior represents ominous advances in the evolution of modern

malware: the use of more sophisticated stealth scanning strategies by millions of coordinated

bots, targeting critical voice communications infrastructure. This work offers a detailed

dissection of the botnet‛s scanning behavior, including general methods to correlate, visualize,

and extrapolate botnet behavior across the global Internet.

53. Learning-Based Uplink Interference Management in 4G LTE Cellular Systems

LTE's uplink (UL) efficiency critically depends on how the interference across different cells is

controlled. The unique characteristics of LTE's modulation and UL resource assignment poses

considerable challenges in achieving this goal because most LTE deployments have 1:1

frequency reuse, and the uplink interference can vary considerably across successive time-slots.

In this paper, we propose LeAP, a measurement data-driven machine learning paradigm for

power control to manage uplink interference in LTE. The data-driven approach has the inherent

advantage that the solution adapts based on network traffic, propagation, and network topology,

which is increasingly heterogeneous with multiple cell-overlays. LeAP system design consists of

the following components: 1) design of user equipment (UE) measurement statistics that are

succinct, yet expressive enough to capture the network dynamics, and 2) design of two learning-

based algorithms that use the reported measurements to set the power control parameters and

optimize the network performance. LeAP is standards-compliant and can be implemented in a

centralized self-organized networking (SON) server resource (cloud). We perform extensive

evaluations using radio network plans from a real LTE network operational in a major metro area

in the US. Our results show that, compared to existing approaches, LeAP provides 4.9× gain in

the 20th percentile of user data rate, 3.25× gain in median data rate.

54. DTN-FLOW: Inter-Landmark Data Flow for High-Throughput Routing in DTNs

In this paper, we focus on the efficient routing of data among different areas in Delay Tolerant

Networks (DTNs). In current algorithms, packets are forwarded gradually through nodes with

higher probability of visiting the destination node or area. However, the number of such nodes

usually is limited, leading to insufficient throughput performance. To solve this problem, we

propose an inter-landmark data routing algorithm, namely DTN-FLOW. It selects popular places

that nodes visit frequently as landmarks and divides the entire DTN area into sub-areas

represented by landmarks. Nodes transiting between landmarks relay packets among landmarks,

even though they rarely visit the destinations of these packets. Specifically, the number of node

transits between two landmarks is measured to represent the forwarding capacity between them,

based on which routing tables are built on each landmark to guide packet routing. Each node

predicts its transits based on its previous landmark visiting records using the order-k Markov

predictor. In a packet routing, a landmark determines the next hop landmark based on its routing

table, and forwards the packet to the node with the highest probability of transiting to the

selected landmark. Thus, DTN-FLOW fully utilizes all node movements to route packets along

landmark paths to their destinations. We analyzed two real DTN traces to support the design of

DTN-FLOW. We also deployed a small DTN-FLOW system in our campus for performance

evaluation. This deployment and trace-driven simulation demonstrate the high efficiency of

DTN-FLOW in comparison with state-of-the-art DTN routing algorithms.

55. DTN-Meteo: Forecasting the Performance of DTN Protocols Under Heterogeneous Mobility

Opportunistic or delay-tolerant networks (DTNs) may be used to enable communication in case

of failure or lack of infrastructure (disaster, censorship, remote areas) and to complement

existing wireless technologies (cellular, WiFi). Wireless peers communicate when in contact,

forming an impromptu network, whose connectivity graph is highly dynamic and only partly

connected. In this harsh environment, communication algorithms are mostly local search

heuristics, choosing a solution among the locally available ones. Furthermore, they are routinely

evaluated through simulations only, as they are hard to model analytically. Even when more

insight is sought from models, these usually assume homogeneous node meeting rates, thereby

ignoring the attested heterogeneity and nontrivial structure of human mobility. We propose

DTN-Meteo, a new unified analytical model that maps an important class of DTN optimization

problems over heterogeneous mobility/contact models into a Markov chain traversal over the

relevant solution space. (Heterogeneous) meeting probabilities between different pairs of nodes

dictate the chain's transition probabilities and determine neighboring solutions. Local

optimization algorithms can accept/reject candidate transitions (deterministically or randomly),

thus “modulating” the above transition probabilities. We apply our model to two example

problems: routing and content placement. We predict the performance of state-of-the-art

algorithms (SimBet, BubbleRap) in various real and synthetic mobility scenarios and show that

surprising precision can be achieved against simulations, despite the complexity of the problems

and diversity of settings. To our best knowledge, this is the first analytical work that can

accurately predict performance for utility-based algorithms and heterogeneous node contact

rates.

56. Analysis of Application-Layer Filtering Policies With Application to HTTP

Application firewalls are increasingly used to inspect upper-layer protocols (as HTTP) that are

the target or vehicle of several attacks and are not properly addressed by network firewalls. Like

other security controls, application firewalls need to be carefully configured, as errors have a

significant impact on service security and availability. However, currently no technique is

available to analyze their configuration for correctness and consistency. This paper extends a

previous model for analysis of packet filters to the policy anomaly analysis in application

firewalls. Both rule-pair and multirule anomalies are detected, hence reducing the likelihood of

conflicting and suboptimal configurations. The expressiveness of this model has been

successfully tested against the features of Squid, a popular Web caching proxy offering various

access control capabilities. The tool implementing this model has been tested on various

scenarios and exhibits good performance.

57. A Graph-Theoretic Approach to Scheduling in Cognitive Radio Networks

We focus on throughput-maximizing, max-min fair, and proportionally fair scheduling problems

for centralized cognitive radio networks. First, we propose a polynomial-time algorithm for the

throughput-maximizing scheduling problem. We then elaborate on certain special cases of this

problem and explore their combinatorial properties. Second, we prove that the max-min fair

scheduling problem is NP-Hard in the strong sense. We also prove that the problem cannot be

approximated within any constant factor better than 2 unless P=NP. Additionally, we propose an

approximation algorithm for the max-min fair scheduling problem with approximation ratio

depending on the ratio of the maximum possible data rate to the minimum possible data rate of a

secondary users. We then focus on the combinatorial properties of certain special cases and

investigate their relation with various problems such as the multiple-knapsack, matching,

terminal assignment, and Santa Claus problems. We then prove that the proportionally fair

scheduling problem is NP-Hard in the strong sense and inapproximable within any additive

constant less than log(4/3). Finally, we evaluate the performance of our approximation algorithm

for the max-min fair scheduling problem via simulations. This approach sheds light on the

complexity and combinatorial properties of these scheduling problems, which have high practical

importance in centralized cognitive radio networks.

58. A Traffic Load Balancing Framework for Software-Defined Radio Access Networks Powered by Hybrid Energy Sources

Dramatic mobile data traffic growth has spurred a dense deployment of small cell base stations

(SCBSs). Small cells enhance the spectrum efficiency and thus enlarge the capacity of mobile

networks. Although SCBSs consume much less power than macro BSs (MBSs) do, the overall

power consumption of a large number of SCBSs is phenomenal. As the energy harvesting

technology advances, base stations (BSs) can be powered by green energy to alleviate the on-

grid power consumption. For mobile networks with high BS density, traffic load balancing is

critical in order to exploit the capacity of SCBSs. To fully utilize harvested energy, it is desirable

to incorporate the green energy utilization as a performance metric in traffic load balancing

strategies. In this paper, we have proposed a traffic load balancing framework that strives a

balance between network utilities, e.g., the average traffic delivery latency, and the green energy

utilization. Various properties of the proposed framework have been derived. Leveraging the

software-defined radio access network architecture, the proposed scheme is implemented as a

virtually distributed algorithm, which significantly reduces the communication overheads

between users and BSs. The simulation results show that the proposed traffic load balancing

framework enables an adjustable trade-off between the on-grid power consumption and the

average traffic delivery latency, and saves a considerable amount of on-grid power, e.g., 30%, at

a cost of only a small increase, e.g., 8%, of the average traffic delivery latency.

59. Wireless Network Intrinsic Secrecy

Wireless secrecy is essential for communication confidentiality, health privacy, public safety,

information superiority, and economic advantage in the modern information society.

Contemporary security systems are based on cryptographic primitives and can be complemented

by techniques that exploit the intrinsic properties of a wireless environment. This paper develops

a foundation for design and analysis of wireless networks with secrecy provided by intrinsic

properties such as node spatial distribution, wireless propagation medium, and aggregate

network interference. We further propose strategies that mitigate eavesdropping capabilities, and

we quantify their benefits in terms of network secrecy metrics. This research provides insights

into the essence of wireless network intrinsic secrecy and offers a new perspective on the role of

network interference in communication confidentiality.

60. FMTCP: A Fountain Code-Based Multipath Transmission Control Protocol

Ideally, the throughput of a Multipath TCP (MPTCP) connection should be as high as that of

multiple disjoint single-path TCP flows. In reality, the throughput of MPTCP is far lower than

expected. In this paper, we conduct an extensive simulation-based study on this phenomenon,

and the results indicate that a subflow experiencing high delay and loss severely affects the

performance of other subflows, thus becoming the bottleneck of the MPTCP connection and

significantly degrading the aggregate goodput. To tackle this problem, we propose Fountain

code-based Multipath TCP (FMTCP), which effectively mitigates the negative impact of the

heterogeneity of different paths. FMTCP takes advantage of the random nature of the fountain

code to flexibly transmit encoded symbols from the same or different data blocks over different

subflows. Moreover, we design a data allocation algorithm based on the expected packet arriving

time and decoding demand to coordinate the transmissions of different subflows. Quantitative

analyses are provided to show the benefit of FMTCP. We also evaluate the performance of

FMTCP through ns-2 simulations and demonstrate that FMTCP outperforms IETF-MPTCP, a

typical MPTCP approach, when the paths have diverse loss and delay in terms of higher total

goodput, lower delay, and jitter. In addition, FMTCP achieves high stability under abrupt

changes of path quality.

61. Backpressure Delay Enhancement for Encounter-Based Mobile Networks While Sustaining Throughput Optimality

Backpressure routing, in which packets are preferentially transmitted over links with high queue

differentials, offers the promise of throughput-optimal operation for a wide range of

communication networks. However, when traffic load is low, backpressure methods suffer from

long delays. This is of particular concern in intermittent encounter-based mobile networks which

are already delay-limited due to the sparse and highly dynamic network connectivity. While state

of the art mechanisms for such networks have proposed the use of redundant transmissions to

improve delay, they do not work well when traffic load is high. In this paper we propose

backpressure with adaptive redundancy (BWAR), a novel hybrid approach that provides the best

of both worlds. This approach is robust, distributed, and does not require any prior knowledge of

network load conditions. We also present variants of BWAR that remove redundant packets via a

timeout mechanism, and that improve energy use. These algorithms are evaluated by

mathematical analysis and by simulations of real traces of taxis in Beijing, China. The

simulations confirm that BWAR outperforms traditional backpressure at low load, while

outperforming encounter-routing schemes (Spray and Wait and Spray and Focus) at high load.

62. A Poisson Hidden Markov Model for Multiview Video Traffic

Multiview video has recently emerged as a means to improve user experience in novel

multimedia services. We propose a new stochastic model to characterize the traffic generated by

a Multiview Video Coding (MVC) variable bit-rate source. To this aim, we resort to a Poisson

hidden Markov model (P-HMM), in which the first (hidden) layer represents the evolution of the

video activity and the second layer represents the frame sizes of the multiple encoded views. We

propose a method for estimating the model parameters in long MVC sequences. We then present

extensive numerical simulations assessing the model's ability to produce traffic with realistic

characteristics for a general class of MVC sequences. We then extend our framework to network

applications where we show that our model is able to accurately describe the sender and receiver

buffers behavior in MVC transmission. Finally, we derive a model of user behavior for

interactive view selection, which, in conjunction with our traffic model, is able to accurately

predict actual network load in interactive multiview services.

63. Backoff Design for IEEE 802.11 DCF Networks: Fundamental Tradeoff and Design Criterion

Binary Exponential Backoff (BEB) is a key component of the IEEE 802.11 DCF protocol. It has

been shown that BEB can achieve the theoretical limit of throughput as long as the initial backoff

window size is properly selected. It, however, suffers from significant delay degradation when

the network becomes saturated. It is thus of special interest for us to further design backoff

schemes for IEEE 802.11 DCF networks that can achieve comparable throughput as BEB, but

provide better delay performance. This paper presents a systematic study on the effect of backoff

schemes on throughput and delay performance of saturated IEEE 802.11 DCF networks. In

particular, a backoff scheme is defined as a sequence of backoff window sizes {Wi}. The

analysis shows that a saturated IEEE 802.11 DCF network has a single steady-state operating

point as long as {Wi} is a monotonic increasing sequence. The maximum throughput is found to

be independent of {Wi}, yet the growth rate of {Wi} determines a fundamental tradeoff between

throughput and delay performance. For illustration, Polynomial Backoff is proposed, and the

effect of polynomial power x on the network performance is characterized. It is demonstrated

that Polynomial Backoff with a larger x is more robust against the fluctuation of the network

size, but in the meanwhile suffers from a larger second moment of access delay. Quadratic

Backoff (QB), i.e., Polynomial Backoff with x=2, stands out to be a favorable option as it strikes

a good balance between throughput and delay performance. The comparative study between QB

and BEB confirms that QB well preserves the robust nature of BEB and achieves much better

queueing performance than BEB.

64. Connectivity-Based Segmentation in Large-Scale 2-D/3-D Sensor Networks: Algorithm and Applications

Efficient sensor network design requires a full understanding of the geometric environment in

which sensor nodes are deployed. In practice, a large-scale sensor network often has a complex

and irregular topology, possibly containing obstacles/holes. Convex network partitioning, also

known as convex segmentation, is a technique to divide a network into convex regions in which

traditional algorithms designed for a simple network geometry can be applied. Existing

segmentation algorithms heavily depend on concave node detection, or sink extraction from the

median axis/skeleton, resulting in sensitivity of performance to network boundary noise.

Furthermore, since they rely on the network's 2-D geometric properties, they do not work for 3-D

cases. This paper presents a novel segmentation approach based on Morse function, bringing

together the notions of convex components and the Reeb graph of a network. The segmentation

is realized by a distributed and scalable algorithm, named CONSEL, for CONnectivity-based

SEgmentation in Large-scale 2-D/3-D sensor networks. In CONSEL, several boundary nodes

first flood the network to construct the Reeb graph. The ordinary nodes then compute mutex

pairs locally, generating a coarse segmentation. Next, neighboring regions that are not mutex

pairs are merged together. Finally, by ignoring mutex pairs that lead to small concavity, we

provide an approximate convex decomposition. CONSEL has a number of advantages over

previous solutions: 1) it works for both 2-D and 3-D sensor networks; 2) it uses merely network

connectivity information; 3) it guarantees a bound for the generated regions' deviation from

convexity. We further propose to integrate network segmentation with existing applications that

are oriented to simple network geometry. Extensive simulations show the efficacy of CONSEL

in segmenting networks and in improving the performance of two applications: geographic

routing and connectivity-based localization.

65. On Asymptotic Statistics for Geometric Routing Schemes in Wireless Ad Hoc Networks

In this paper we present a methodology employing statistical analysis and stochastic geometry to

study geometric routing schemes in wireless ad-hoc networks. In particular, we analyze the

network layer performance of one such scheme, the random \frac{1}{2}disk routing scheme,

which is a localized geometric routing scheme in which each node chooses the next relay

randomly among the nodes within its transmission range and in the general direction of the

destination. The techniques developed in this paper enable us to establish the asymptotic

connectivity and the convergence results for the mean and variance of the routing path lengths

generated by geometric routing schemes in random wireless networks. In particular, we

approximate the progress of the routing path towards the destination by a Markov process and

determine the sufficient conditions that ensure the asymptotic connectivity for both dense and

large-scale ad-hoc networks deploying the random \frac{1}{2}disk routing scheme.

Furthermore, using this Markov characterization, we show that the expected length (hop-count)

of the path generated by the random \frac{1}{2}disk routing scheme normalized by the length of

the path generated by the ideal direct-line routing, converges to 3\pi/4asymptotically. Moreover,

we show that the variance-to-mean ratio of the routing path length converges to 9\pi^2/64-

1 asymptotically. Through simulation, we show that the aforementioned asymptotic statistics are

in fact quite accurate even for finite granularity and size of the network.

66. Efficient Allocation of Periodic Feedback Channels in Broadband Wireless Networks

Advanced wireless technologies such as multiple-input–multiple-output (MIMO) require each

mobile station (MS) to send a lot of feedback to the base station. This periodic feedback

consumes much of the uplink bandwidth. This expensive bandwidth is very often viewed as a

major obstacle to the deployment of MIMO and other advanced closed-loop wireless

technologies. This paper is the first to propose a framework for efficient allocation of periodic

feedback channels to the nodes of a wireless network. Several relevant optimization problems are

defined and efficient algorithms for solving them are presented. A scheme for deciding when the

base station (BS) should invoke each algorithm is also proposed and shown through simulations

to perform very well.

67.  Fast and Accurate Estimation of RFID Tags

Radio frequency identification (RFID) systems have been widely deployed for various

applications such as object tracking, 3-D positioning, supply chain management, inventory

control, and access control. This paper concerns the fundamental problem of estimating RFID

tag population size, which is needed in many applications such as tag identification, warehouse

monitoring, and privacy-sensitive RFID systems. In this paper, we propose a new scheme for

estimating tag population size called Average Run-based Tag estimation (ART). The technique

is based on the average run length of ones in the bit string received using the standardized

framed slotted Aloha protocol. ART is significantly faster than prior schemes. For example,

given a required confidence interval of 0.1% and a required reliability of 99.9%, ART is

consistently 7 times faster than the fastest existing schemes (UPE and EZB) for any tag

population size. Furthermore, ART's estimation time is provably independent of the tag

population sizes. ART works with multiple readers with overlapping regions and can estimate

sizes of arbitrarily large tag populations. ART is easy to deploy because it neither requires

modification to tags nor to the communication protocol between tags and readers. ART only

needs to be implemented on readers as a software module.

68. Achieving Optimal Throughput Utility and Low Delay With CSMA-Like Algorithms: A Virtual Multichannel Approach

Carrier-sense multiple access (CSMA) algorithms have recently received significant interests in

the literature for designing wireless control algorithms. CSMA algorithms incur low complexity

and can achieve the optimal capacity under certain assumptions. However, CSMA algorithms

suffer the starvation problem and incur large delay that may grow exponentially with the network

size. In this paper, our goal is to develop a new algorithm that can provably achieve high

throughput utility and low delay with low complexity. Toward this end, we propose a new

CSMA-like algorithm, called Virtual-Multi-Channel CSMA (VMC-CSMA), that can

dramatically reduce delay. The key idea of VMC-CSMA to avoid the starvation problem is to

use multiple virtual channels (which emulate a multichannel system) and compute a good set of

feasible schedules simultaneously (without constantly switching/recomputing schedules). Under

the protocol interference model and a single-hop utility-maximization setting, VMC-CSMA can

approach arbitrarily close-to-optimal system utility with both the number of virtual channels and

the computation complexity increasing logarithmically with the network size. Furthermore, once

VMC-CSMA converges to the steady state, we can show that under certain assumptions on the

utility functions and the topology, both the expected packet delay and the tail distribution of the

head-of-line (HOL) waiting time at each link can be bounded independently of the network size.

Our simulation results confirm that VMC-CSMA algorithms indeed achieve both high

throughput utility and low delay with low-complexity operations.

69. Receiver-Based Flow Control for Networks in Overload

We consider utility maximization in networks where the sources do not employ flow control and

may consequently overload the network. In the absence of flow control at the sources, some

packets will inevitably have to be dropped when the network is in overload. To that end, we first

develop a distributed, threshold-based packet-dropping policy that maximizes the weighted sum

throughput. Next, we consider utility maximization and develop a receiver-based flow control

scheme that, when combined with threshold-based packet dropping, achieves the optimal utility.

The flow control scheme creates virtual queues at the receivers as a push-back mechanism to

optimize the amount of data delivered to the destinations via back-pressure routing. A new

feature of our scheme is that a utility function can be assigned to a collection of flows,

generalizing the traditional approach of optimizing per-flow utilities. Our control policies use

finite-buffer queues and are independent of arrival statistics. Their near-optimal performance is

proved and further supported by simulation results.

70. Offering Supplementary Network Technologies: Adoption Behavior and Offloading Benefits

To alleviate the congestion caused by rapid growth in demand for mobile data, wireless service

providers (WSPs) have begun encouraging users to offload some of their traffic onto

supplementary network technologies, e.g., offloading from 3G or 4G to WiFi or femtocells. With

the growing popularity of such offerings, a deeper understanding of the underlying economic

principles and their impact on technology adoption is necessary. To this end, we develop a model

for user adoption of a base technology (e.g., 3G) and a bundle of the base plus a supplementary

technology (e.g., 3G + WiFi). Users individually make their adoption decisions based on several

factors, including the technologies' intrinsic qualities, negative congestion externalities from

other subscribers, and the flat access rates that a WSP charges. We then show how these user-

level decisions translate into aggregate adoption dynamics and prove that these converge to a

unique equilibrium for a given set of exogenously determined system parameters. We fully

characterize these equilibria and study adoption behaviors of interest to a WSP. We then derive

analytical expressions for the revenue-maximizing prices and optimal coverage factor for the

supplementary technology and examine some resulting nonintuitive user adoption behaviors.

Finally, we develop a mobile app to collect empirical 3G/WiFi usage data and numerically

investigate the profit-maximizing adoption levels when a WSP accounts for its cost of deploying

the supplemental technology and savings from offloading traffic onto this technology.

71. On the Delay Performance in a Large-Scale Wireless Sensor Network: Measurement, Analysis, and Implications

We present a comprehensive delay performance measurement and analysis in a large-scale

wireless sensor network. We build a lightweight delay measurement system and present a robust

method to calculate the per-packet delay. We show that the method can identify incorrect delays

and recover them with a bounded error. Through analysis of delay and other system metrics, we

seek to answer the following fundamental questions: What are the spatial and temporal

characteristics of delay performance in a real network? What are the most important impacting

factors, and is there any practical model to capture those factors? What are the implications to

protocol designs? In this paper, we identify important factors from the data trace and show that

the important factors are not necessarily the same with those in the Internet. Furthermore, we

propose a delay model to capture those factors. We revisit several prevalent protocol designs

such as Collection Tree Protocol, opportunistic routing, and Dynamic Switching-based

Forwarding and show that our model and analysis are useful to practical protocol designs.

72. Scheduling in Networks With Time-Varying Channels and Reconfiguration Delay

We consider the optimal control problem for networks subjected to time-varying channels,

reconfiguration delays, and interference constraints. We show that the simultaneous presence of

time-varying channels and reconfiguration delays significantly reduces the system stability

region and changes the structure of optimal policies. We first consider memoryless channel

processes and characterize the stability region in closed form. We prove that a frame-based Max-

Weight scheduling algorithm that sets frame durations dynamically, as a function of the current

queue lengths and average channel gains, is throughput-optimal. Next, we consider arbitrary

Markov-modulated channel processes and show that memory in the channel processes can be

exploited to improve the stability region. We develop a novel approach to characterizing the

stability region of such systems using state-action frequencies, which are stationary solutions to a

Markov Decision Process (MDP) formulation. Moreover, we develop a dynamic control policy

using the state-action frequencies and variable frames whose lengths are functions of queue sizes

and show that it is throughput-optimal. The frame-based dynamic control (FBDC) policy is

applicable to a broad class of network control systems, with or without reconfiguration delays,

and provides a new framework for developing throughput-optimal network control policies using

state-action frequencies. Finally, we propose Myopic policies that are easy to implement and

have better delay properties as compared to the FBDC policy.

73. Capacity Achieving Distributed Scheduling With Finite Buffers

In this paper, we propose a distributed cross-layer scheduling algorithm for wireless networks

with single-hop transmissions that can guarantee finite buffer sizes and meet minimum utility

requirements. The algorithm can achieve a utility arbitrarily close to the optimal value with a

tradeoff in the buffer sizes. The finite buffer property is not only important from an

implementation perspective, but, along with the algorithm, also yields superior delay

performance. In addition, another extended algorithm is provided to help construct the upper

bounds of per-flow average packet delays. A novel structure of Lyapunov function is employed

to prove the utility optimality of the algorithm with the introduction of novel virtual queue

structures. Unlike traditional back-pressure-based optimal algorithms, our proposed algorithm

does not need centralized computation and achieves fully local implementation without global

message passing. Compared to other recent throughput/utility-optimal CSMA distributed

algorithms, we illustrate through rigorous numerical and implementation results that our

proposed algorithm achieves far better delay performance for comparable throughput/utility

levels.

74. Optimizing Data Plane Resources for Multipath Flows

In many modern networks, such as datacenters, optical networks, and multiprotocol label

switching (MPLS), the delivery of a traffic flow with a certain bandwidth demand over a single

network path is either not possible or not cost-effective. In these cases, it is very often possible to

improve the network's bandwidth utilization by splitting the traffic flow over multiple efficient

paths. While using multiple paths for the same traffic flow increases the efficiency of the

network, it consumes expensive forwarding resources from the network nodes, such as TCAM

entries of Ethernet/MPLS switches and wavelengths/lightpaths of optical switches. In this paper,

we define several problems related to splitting a traffic flow over multiple paths while

minimizing the consumption of forwarding resources, and present efficient algorithms for

solving these problems.

75. Multipath TCP: Analysis, Design, and Implementation

Multi-path TCP (MP-TCP) has the potential to greatly improve application performance by using

multiple paths transparently. We propose a fluid model for a large class of MP-TCP algorithms

and identify design criteria that guarantee the existence, uniqueness, and stability of system

equilibrium. We clarify how algorithm parameters impact TCP-friendliness, responsiveness, and

window oscillation and demonstrate an inevitable tradeoff among these properties. We discuss

the implications of these properties on the behavior of existing algorithms and motivate a new

design that generalizes existing algorithms and strikes a good balance among TCP-friendliness,

responsiveness, and window oscillation. We have implemented our algorithm in the Linux

kernel. We use our prototype to compare the new algorithm with existing MP-TCP algorithms.

76. Analysis and Experimental Verification of Frequency-Based Interference Avoidance Mechanisms in IEEE 802.15.4

More and more wireless networks are deployed with overlapping coverage. Especially in the

unlicensed bands, we see an increasing density of heterogeneous solutions, with very diverse

technologies and application requirements. As a consequence, interference from heterogeneous

sources-also called cross-technology interference-is a major problem causing an increase of

packet error rate (PER) and decrease of quality of service (QoS), possibly leading to application

failure. This issue is apparent, for example, when an IEEE 802.15.4 wireless sensor network

coexists with an IEEE 802.11 wireless LAN, which is the focus of this work. One way to

alleviate cross-technology interference is to avoid it in the frequency domain by selecting

different channels. Different multichannel protocols suitable for frequency-domain interference

avoidance have already been proposed in the literature. However, most of these protocols have

only been investigated from the perspective of intratechnology interference. Within this work,

we create an objective comparison of different candidate channel selection mechanisms based on

a new multichannel protocol taxonomy using measurements in a real-life testbed. We assess

different metrics for the most suitable mechanism using the same set of measurements as in the

comparison study. Finally, we verify the operation of the best channel selection metric in a

proof-of-concept implementation running on the testbed.

77. Joint Scheduling and Fast Cell Selection in OFDMA Wireless Networks

In modern broadband cellular networks, the omnidirectional antenna at each cell is replaced by

three or six directional antennas, one in every sector. While every sector can run its own

scheduling algorithm, bandwidth utilization can be significantly increased if a joint scheduler

makes these decisions for all the sectors. This gives rise to a new problem, referred to as “joint

scheduling,” addressed in this paper for the first time. The problem is proven to be NP-hard, but

we propose efficient algorithms with a worst-case performance guarantee for solving it. We then

show that the proposed algorithms indeed substantially increase the network throughput.

78. AWG-Based Non-Blocking Clos Networks

The three-stage Clos networks remain the most popular solution to many practical switching

systems to date. The aim of this paper is to show that the modular structure of Clos networks is

invariant with respect to the technological changes. Due to the wavelength routing property of

arrayed-waveguide gratings (AWGs), non-blocking and contention-free wavelength-division-

multiplexing (WDM) switches require that two calls carried by the same wavelength must be

connected by separated links; otherwise, they must be carried by different wavelengths. Thus, in

addition to the non-blocking condition, the challenge of the design of AWG-based multistage

switching networks is to scale down the wavelength granularity and to reduce the conversion

range of tunable wavelength converters (TWCs). We devise a logic scheme to partition the

WDM switch network into wavelength autonomous cells and show that the wavelength

scalability problem can be solved by recursively reusing similar, but smaller, set of wavelengths

in different cells. Furthermore, we prove that the rearrangeably non-blocking (RNB) condition

and route assignments in these AWG-based three-stage networks are consistent with that of

classical Clos networks. Thus, the optimal AWG-based non-blocking Clos networks also can

achieve 100% utilization when all input and output wavelength channels are busy.

79. Whispers in the Hyper-Space: High-Bandwidth and Reliable Covert Channel Attacks Inside the Cloud

Privacy and information security in general are major concerns that impede enterprise adaptation

of shared or public cloud computing. Specifically, the concern of virtual machine (VM) physical

co-residency stems from the threat that hostile tenants can leverage various forms of side

channels (such as cache covert channels) to exfiltrate sensitive information of victims on the

same physical system. However, on virtualized x86 systems, covert channel attacks have not yet

proven to be practical, and thus the threat is widely considered a “potential risk.” In this paper,

we present a novel covert channel attack that is capable of high-bandwidth and reliable data

transmission in the cloud. We first study the application of existing cache channel techniques in a

virtualized environment and uncover their major insufficiency and difficulties. We then

overcome these obstacles by: (1) redesigning a pure timing-based data transmission scheme, and

(2) exploiting the memory bus as a high-bandwidth covert channel medium. We further design

and implement a robust communication protocol and demonstrate realistic covert channel attacks

on various virtualized x86 systems. Our experimental results show that covert channels do pose

serious threats to information security in the cloud. Finally, we discuss our insights on covert

channel mitigation in virtualized environments.

80. Fair Virtualization of 802.11 Networks

We consider virtualization of network capacity in 802.11 WLANs and mesh networks. We show

that allocating total airtime slices to ISPs is analogous to allocating a fraction of available time-

slots in TDMA. We establish that the max-min fair flow rate allocation within an ISP airtime

slice can be characterized independently of the rate allocation policy employed in other slices.

Building on these observations, we present a lightweight, distributed algorithm for allocating

airtime slices among ISP and max-min fair flow rates within each slice.

81. Maximizing Submodular Set Function With Connectivity Constraint: Theory and Application to Networks

In this paper, we investigate the wireless network deployment problem, which seeks the best

deployment of a given limited number of wireless routers. We find that many goals for network

deployment, such as maximizing the number of covered users, the size of the coverage area, or

the total throughput of the network, can be modeled with a submodular set function. Specifically,

given a set of routers, the goal is to find a set of locations S, each of which is equipped with a

router, such that S maximizes a predefined submodular set function. However, this deployment

problem is more difficult than the traditional maximum submodular set function problem, e.g.,

the maximum coverage problem, because it requires all the deployed routers to form a connected

network. In addition, deploying a router in different locations might consume different costs. To

address these challenges, this paper introduces two approximation algorithms, one for

homogeneous deployment cost scenarios and the other for heterogeneous deployment cost

scenarios. Our simulations, using synthetic data and real traces of census in Taipei, Taiwan,

show that the proposed algorithms achieve better performances than other heuristics.

82. Adapting Cellular Networks to Whitespaces Spectrum

TV Whitespaces, recently opened up by the Federal Communications Commission (FCC) for

unlicensed use, are seen as a potential cellular offload and/or standalone mechanism, especially

in dense metros where the demand for throughput is high. In this paper, we use real data

collected from whitespaces databases to empirically demonstrate features unique to whitespaces-

power-spectrum tradeoff and spatial variation in spectrum availability. From this study, we

conclude the need for whitespaces-specific adaptations to cellular networks so as to be able to

extract maximum throughput and guarantee reliability. To tackle the effects of the power-

spectrum tradeoff, we propose a novel base-station design that specifically uses low-power

transmitters as a means to maximize throughput. This design co-locates and networks together

many low-powered mode-I devices to act as a multiple-antenna array. We estimate the size of the

array required to meet typical rate targets, and show that the array design significantly

outperforms traditional designs in terms of throughput for a given cost. We then turn our

attention to spatial variability and study its impact on the problem of locating base stations in a

whitespaces network. Here, we propose spectrum-aware placement algorithms for whitespaces,

which account for this spatial variability along with key parameters like user density. We show

that such algorithms clearly outperform traditional placement algorithms and improve network

coverage in this band.

83. Optimal Slot Assignment for Binary Tracking Tree Protocol in RFID Tag Identification

Tag anti-collision has long been an important issue in RFID systems. To accelerate tag

identification, some researchers have recently adopted bit tracking technology that allows the

reader to detect the locations of collided bits in a collision slot. However, these methods still

encounter the problem of too many collisions occurring at the beginning of identification. This

paper proposes an optimal binary tracking tree protocol (OBTT) that tries to separate all of the

tags into smaller sets to reduce collisions at the beginning of identification. Using bit tracking

technology, OBTT mainly adopts three proposed approaches, bit estimation, optimal partition,

and binary tracking tree. Bit estimation first estimates the number of tags based on the locations

of collided bits. Optimal partition then determines the optimal number of the initial sets based on

this estimation. Binary tracking tree lets the tag utilize one counter to achieve the split during the

identification process. This paper formally analyzes the slot efficiency of OBTT, which

represents how many tags can be identified in a slot. Results show that the slot efficiency is close

to 0.614, the highest value published to date. Considering slot lengths, OBTT further determines

the optimal number of the initial sets to minimize the identification delay. The analytical results

show that the delay efficiency of OBTT achieves 0.750, where delay efficiency represents the

number of tags that can be identified in a baseline slot, the length of which is the complete ID

sent by the tag. The simulation results show that OBTT outperforms other existing algorithms.

84. Evolution of the Internet Economic Ecosystem

The evolution of the Internet has manifested itself in many ways: the traffic characteristics, the

interconnection topologies, and the business relationships among the autonomous components. It

is important to understand why (and how) this evolution came about, and how the interplay of

these dynamics may affect future evolution and services. We propose a network-aware,

macroscopic model that captures the characteristics and interactions of the application and

network providers, and show how it leads to a market equilibrium of the ecosystem. By

analyzing the driving forces and the dynamics of the market equilibrium, we obtain some

fundamental understandings of the cause and effect of the Internet evolution, which explain why

some historical and recent evolutions have happened. Furthermore, by projecting the likely

future evolutions, our model can help application and network providers to make informed

business decisions so as to succeed in this competitive ecosystem.