Data Dissemination for Spot Applications in Ad-Hoc Networks

Alaeddine EL-FAWALThesis director :

Jean-Yves Le Boudec

Private Defense, 3 April 2009, EPFL

Overview on the PhD Work

Supported by 2 projects: Haggle: European project in Situated and Autonomic Communications

NCCR MICS: National Center of Competence in Research – Mobile Information and Communication Systems

2 parts in my PhD work: Data dissemination for spot applications over WIFI technology (Haggle)

Cross-layer optimization for UWB systems (MICS)

Dealing with different facets of uncoordinated ad-hoc wirelessnetworks and deals with challenges at all networking layers

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OUTLINE

Introduction

Conclusions

Prototyping and Testbed

SLEF: Our Data Dissemination Middleware

Performance Validation

Achievements

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Open-Ended Environment

Caused by:Dramatic expansion of WIFI interfaces: laptops, PDAs, mobile phones, video games and even with peripherals and vehicles.

Characteristics: Involves from few to thousands of nodes.

Challenging circumstances: Highly dynamic Unpredictable Uncoordinated Short contact time Quickly changing from dense to sparse, non-congested to congested

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Destination: all nodes within the spot (multi-hop).

The spot might be the entire network (campus).

Example: ad applications, traffic info, support routing, resource discovery, bootstrapping phases for application layer.

Spot ApplicationsDescription

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Efficient and reliable data dissemination service

Trade-off: spread-application rateSpread: number of nodes within the application spot

(number of nodes that receive a packet). The spot size is variable according to the network conditions.

Delivery ratio can not be used… instead, we talk about spread.

Requirements:

Spot Applications

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Open-Ended Envir. : Variation and Diversity of Scenarios

Transmission range

Density: average

Few sources: little new injected traffic

Relay

Source / Relay

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Transmission range

Density: average

almost all are sources: a lot of new injected traffic

Relay

Source / Relay

Open-Ended Envir. : Variation and Diversity of Scenarios

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Relay

Source / Relay

Very high density (traffic jam)

almost all are sources: a huge amount of new injected traffic

One hop: + 200 neighbors

Open-Ended Envir. : Variation and Diversity of Scenarios

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Relay

Source / Relay

An autonomic mechanism for data dissemination that adapts tothis diversity in scenarios is a must, otherwise

network failure

Density: very sparse.

No communication without mobility (opportunistic communication)

Open-Ended Envir. : Variation and Diversity of Scenarios

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OUTLINE

Introduction

Conclusions

Prototyping and Testbed

SLEF: Our Data Dissemination Middleware

Performance Validation

Achievements

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Data dissemination through limited epidemic forwarding :

A source transmits packets in broadcast mode.Nodes forward each packet they receive Forwarding Factor

times.Packets are forwarded within a limited hop count.

SLEF: Self Limiting Epidemic Forwarding

We propose the SLEF middleware.

Delivers an efficient and reliable data dissemination service to the spot applications

Deals with the tradeoff: spread-application rate

The network conditions define the TTL limit (spread control).

Functional between the application and the transmission sockets (UDP or raw sockets).

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SLEF: Self Limiting Epidemic Forwarding

SLEF is designed to hold in all scenarios, in particular in very dense and very sparse ones

SLEF Features:

Autonomic: Adapts itself to any change in the network.

Density increases forwarding factor decreases

Traffic load increases TTL limit decreases

Complete design of a middleware

Does not need / exchange any topology information. Uses only local information to the node (very short contact time).

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Essential Functions for Multi-Hop BroadcastSLEF implements 6 essential functions needed for a sustainable service 1. Congestion control: first mechanism proposed for broadcast in ad

hoc networks

4. Spread control (adaptive TTL)

5. Forwarding factor control

6. Buffer management

2. Efficient use of MAC broadcast: 802.11 broadcast does not implement any exclusion mechanism

(RTS/CTS) and it performs poorly (similar to Aloha). We replace it by a new scheme that we call pseudo-broadcast.

802.11 broadcast does not implement Ack. Pkts might be transmitted in the vacuum. We implement a presence indicator that does not need any message exchange.

3. Scheduler / fairness: A scheduler is needed to decide which packet to serve. It is based on Source ID to ensure some level of fairness.

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Spread Control: Adaptive TTLTrade-Off Spread vs. Application RateSpread: number of nodes that receive a packet.

N : Spread

FF: Forwarding Factor

R0: Nominal Rate of MAC Layer

λ : Application Rate

We use an Aging mechanism

Adaptive TTL: Aging adapts locally the TTL to the different network setting, based on the send/receive events.

The idea is as follows:

How:

TTL limit= 2

Density =>TTL : In a traffic jam: TTL = 1

Density => TTL : In a very sparse network: TTL = 10

With SLEF

Density => Spread Rate

With fixed TTL

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Aging New created pkt: Age = 0 Pkt received for the first time: Age = 255 – TTL Age manipulated locally. when transmitting: TTL = 255 -Age

Hop count: plays the role of a fixed TTL (=255/K0) if the network is not congested.Adaptive Age: adapts the TTL to the network activity, which reflects the density and the traffic loadReal time Age: A pkt lives at most 8 hours (work cycle).

Age

Send/receive the same pktAge = Age + K0

receive any pktAge = Age + K1

Age > 255

Drop packet

Constant increaseby time: 8h -> 255

hop count adaptive Age

Real time Age

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Spread-Rate Balance

SLEF maintains a spread-rate balance

2 parameters to adjust: K0, K1

Once Adjusted, they work well with all settings

Adjusting the spread-rate balance

according to the application needs

Default values for K0 and K1 are computed

in the thesis

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Why: To Minimize redundancy (save resources)

Transmission would be redundant

One send/receive event

Two send/receive events:

The green nodes are inhibited: smaller forwarding factor

Inhibit nodes from transmitting over sent/received pkts.

We compute a virtual rate for each packet based on the send/receive events.

Adaptive: the virtual rate Adapts locally the Forwarding Factor to the different network settings

Forwarding Factor Control

How:

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3- The pkt is allowed to be transmitted only after: current time +

(similar to a back-off system)

Virtual Rate

The smaller the vRate is, the longer the back-off time is: The pkt might be dropped before being transmitted

Virtual Rate: The max rate a packet is transmitted with

R0 : nominal MAC rate [pkts/s]RcvCount : number of times the pkt is receivedSendCount : number of times the pkt is senta and b : are coefficient less than 1: a=0.1, b=0.01

For each send / receive event on a given pkt:1- The virtual rate is computed as follows:

Unlike other mechanisms, the virtual rate based forwarding factor control allows transmitting the pkt multiple times if needed.

2- vRate decreases exponentially with send/receive events.

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Buffer Management

Cleans the buffer in order to keep space for new incoming packets.

Based on Aging.

Drops packets with the highest age

Highest age

Lived the highest number of send/receive events

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OUTLINE

Introduction

Conclusions

Prototyping and Testbed

SLEF: Our Data Dissemination Middleware

Performance Validation

Achievements

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Network Simulator: JIST-SWANS, A JAVA simulator for Ad Hoc networks

MAC : 802.11/b

Channel : Fading

Setting

Scenarios:

• Vehicular networks.

• Different network settings: node density, traffic load…

Vehicular Mobility Simulator: STRAW, an extension of JIST-SWANS. It provides a mobility model based on the operation of the real vehicular traffic.

Topo : 2-lanes road, speed limit 80Km/h

Range : 300 m in average

K0 = 25

K1 = 0.1

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Adaptation of the Spread to the Rate

Rate Spread

Adaptive TTL

Density: 12 vehicles/Km

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Adaptation of the Forwarding Factor to the Density

Very dense (Traffic jam)+200 neighbors

Very sparse

(Death Valley)

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Importance of the Pseudo-Broadcast

Very dense (Traffic jam): +200 neighbors

Idea: implement a mutual exclusion mechanism for broadcast in order to avoid collision

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OUTLINE

Introduction

Conclusions

Prototyping and Testbed

SLEF: Our Data Dissemination Middleware

Performance Validation

Achievements

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SLEF Prototyping 2 architectures:

MAC

Spot application

SLEF

Spot application

SLEF

UDP

IP

MAC

+ It is independent of the IP address

+ Practical in the absence of a centralized coordination where assigning IP @ is challenging

– Complex with Windows

– IP networking needs to be initialized

+Straightforward with all platforms

Raw sockets

UDP sockets

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SLEF Prototyping 4 platforms:

Windows XP: J2SE, C++

Windows Mobile: J2ME, C++

Linux: J2SE, C++

OpenWrt (Linux-like firmware for embedded system): C++

Resource-constrained devices: Smartphone HTC S620:

Windows Mobile

64MB RAM, 128 ROM

201 MHz

ASUS WL-500 GP wireless router

OpenWrt

32MB RAM, 8MB Flash

266MHz

SLEF is practical and performs well on very resource-limited devices

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Testbed Stress test: More than 50 devices communicating with each other for long time. Performance evaluation of SLEF through measurements Testbed features: Wireless router: ASUS WL-500GP

Technical specifications: 8MB Flash, 32MB RAM, 266MHz, 2 USB 2.0 ports

Firmware: OpenWrt

Configurable wireless interface: using Atheros card with MadWIFI driver (setting RTS/CTS Th, Tx power, promiscuous mode, monitor mode, Tx queue length…).

Mobility: using plumb batteries, +4 hrs lifetime with full power transmission at full rate

Robustness.

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Measurement DesignNodes are distributed over 12 buildings in EPFL

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Measurement Design

Application: injects packets at fixed rate.

Application rate: can be reduced by the congestion control mechanism.

Comparison: SLEF vs. fixed-TTL

Buffer size of fixed-TTL:

Small buffer size: We ran SLEF and we use the average buffer occupation obtained (620 packets).

Large buffer size: 10 000 packets.

Fixed-TTL: Implements all functions of SLEF, otherwise it is not functional. Spread control is replaced by TTL (decremented by one for each hop) TTL limit is fixed Buffer management is based on the TTL and not on the age: packets with the smallest TTL are dropped first when the buffer is full Fixed-TTL limits the spread through 2 parameters: TTL limit and the buffer size.

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Measurement Results

With fixed TTL:

Setting the buffer size per scenario is needed:

Large buffer size radundancy and low rate

Small buffer size small spread even in non-congested network TTL based buffer management does not perform well.

Higher redundancy Lower rate

Smaller spread

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Measurement Conclusions

SLEF Fixed-TTL

2 parameters to adjust: K0, K1

Once adjusted, they work well with all settings

Aging based buffer management performs well

Max Buffer size is 255/K1 (little formula)

2 parameters to adjust: MaxTTL and buffer size

Needs to adjust whenever the network setting (density, traffic load, mobility,…) changes

TTL based buffer management performs poorly.

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OUTLINE

Introduction

Conclusions

Prototyping and Testbed

SLEF: Our Data Dissemination Middleware

Performance Validation

Achievements

36

Conclusions

Autonomic: Adapts itself to any change in the network.

Complete middleware

Does not need/exchange any topology information. Uses only local information to the node.

Works even in extreme scenarios (very dense/sparse…)

Performs well on resource constrained devices

We propose SLEF: data dissemination middleware for spot applications

Prototyping SLEF for 4 platforms

Building a testbed for wireless networks protocols

SLEF performs better than fixed-TTL:

Fixed-TTL is not adaptive

TTL-based bufer management performs poorly

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Perspectives

Collaboration with LCA3: Prof. Patrick Thiran and Adel Aziz Extensive series of measurements for wireless network protocols

Performance evaluation of SLEF: Factorial analysis applied on measurement results.

Measurements will consider varying scenarios: mobility, intermittent connectivity, different traffic load and density.

Comparison with different variants of data dissemination protocols

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OUTLINE

Introduction

Conclusions

Prototyping and Testbed

SLEF: Our Data Dissemination Middleware

Performance Validation

Achievements

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Achievements

Multi-Hop Broadcast Middleware (SLEF): One conference paper.

Vulnerabilities in Epidemic Forwarding: One conference paper.

SLEF Prototyping and Experimental Testbed.

Data Dissemination for Spot Applications (Haggle)

Robust Signal Acquisition in UWB Ad Hoc Networks: One journal paper, one conference paper and one patent

(adopted by MICS).

Sleeping Mode for UWB IR Ad-hoc Networks: One journal paper.

Cross-Layer Optimization for UWB IR Networks (MICS)

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Robust Signal Acquisition in UWB Ad Hoc Networks:Problem: Conventional detection method

assume power control, otherwise it fails.

Power control impractical in the absence of a centralized coordination (CDMA).

S1

D2 S2

D1Near-far scenario

Solution: Power independent detection method.

10 users, LOS Indoor Office Channel model by IEEE P802.15.4a

Proba of Misdetection: PMD Total Error: Et=PMD + PFA

PM

D

Performance Evaluation:

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Issues Addressed for the First Time

Spot Applications (introduced for the first time).

Trade-off: Spread – Application rate.

Spread control.

Congestion control in ad-hoc networks in broadcast mode.

Fairness with epidemic forwarding.

Identifying vulnerabilities that are specific to epidemic forwarding.

First prototype of network coding for ad-hoc networks.

Power independent signal acquisition for UWB in uncoordinated wireless ad-hoc networks (problem identification and solution).

Identifying key design elements for power saving with UWB IR systems.

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Used Expertise

Queuing theory

Performance evaluation tools

Wireless networks

Security

All layers of TCP/IP stack, mainly: MAC (Medium Access Control) Physical Layer (UWB IR and 802.11)

Vehicular networks

Network coding

Different channel models

Signal processing.

Simulation ns-2, Jist-Swans, Straw (vehicular traffic simulator), Matlab.

System programming Windows XP, Windows Mobile, Linux, OpenWrt C++, J2SE, J2ME, raw sockets

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Demo: Ad-Hoc Ventes Flash

Spot application

Needs SLEF

Windows platform: XP and Mobile

C++

Sender (shop) Client

Injects ads:

Shop name

Product features:

Name

Category

Price

…

Receive ads:

Filtering at the application level:

Shop name

Category

Vote

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Demo: Ad-Hoc Ventes FlashScenario: Persistent broadcast in presence of intermittent connectivity

Shop Client 1 Client 2

Application on X

XX

Application onApplication off

XXX Application

onApplication off

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List of Publications at EPFL

El Fawal, Alaeddine ; Le Boudec, Jean-Yves: A Robust Signal Detection Method for Ultra Wide Band (UWB) Networks with Uncontrolled Interference. In: IEEE Transactions on Microwave Theory and Techniques (MTT,) 2006.

Raya, Maxim ; Aad, Imad ; Hubaux, Jean-Pierre ; El Fawal, Alaeddine DOMINO: Detecting MAC layer greedy behavior in IEEE 802.11 hotspots. In: IEEE Transactions on Mobile Computing, December 2006

El Fawal, Alaeddine ; Le Boudec, Jean-Yves ; Salamatian, Kave Multi-hop Broadcast from Theory to Reality: Practical Design for Ad Hoc Networks. In: First International Conference on Autonomic Computing and Communication Systems, October 2007.El Fawal, Alaeddine ; Le Boudec, Jean-Yves ; Salamatian, Kave Vulnerabilities in Epidemic Forwarding In: The First IEEE WoWMoM Workshop on Autonomic and Opportunistic Communications (AOC2007), 2007Merz, Ruben ; El Fawal, Alaeddine ; Le Boudec, Jean-Yves ; Radunovic, Bozidar et al. The Optimal MAC Layer for Low-Power UWB is Non-Coordinated. In: IEEE International Symposium on Circuits and Systems (ISCAS 2006), 2006El Fawal, Alaeddine ; Le Boudec, Jean-Yves A Power Independent Detection Method for UltraWide Band (UWB) Impulse Radio Networks. In: IEEE International Conference on Ultra-Wideband (ICU 2005), 2005

El Fawal, Alaeddine ; Le Boudec, Jean-Yves 

Synchronizing Method for Impulse Radio Networks, Date: 2005

El Fawal, Alaeddine ; Le Boudec, Jean-Yves et al. Tradeoff Analysis of PHY-aware MAC in Low-Rate, Low-Power UWB networks. In: IEEE Communications Magazine, vol. 43, num. 12, 2005, p. 147.

Journal Articles:

Proceedings:

Pending Patent:

El Fawal, Alaeddine ; Salamatian, Kave et al. A framework for network coding in challenged wireless network.  Presented at: MobiSys 2006, Uppsala - Sweden, June 19-22, 2006.

Demo

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Testbed Testbed features:Wireless router: ASUS WL-500GP

Technical specifications: 8MB Flash, 32MB RAM, 266MHz, 2 USB 2.0 ports

Firmware: OpenWrt

Configurable wireless interface: using Atheros card with MadWIFI driver (setting RTS/CTS Th, Tx power, Tx queue length…).

Mobility: using plumb batteries, +4 hrs lifetime with full power transmission at full rate

Robustness.