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transcript
Mobile Advanced Networks Introduction
Navid Nikaein
Mobile Communication Department
This work is licensed under a CC attribution Share-Alike 3.0 Unported license.
The Big Picture User Equipments: Multi-Media PCs equipped to send and receive all variety
of multimedia User Communication Equipments: Connects the Users' PC(s) to the "Local
Loop" Local Loop Carriers: Connects the User location to the ISP's Point of Presence
(POP). ISP’s POP: Connections from the user are accepted and authenticated by the
ISP User Services Provided by the ISP: Used by the User for access (DNS, EMAIL,
etc). Core network / ISP backbone: Interconnects the ISP's POPs, AND
interconnects the ISP to other ISP's and online content. Online Contents: These are the host sites / servers that the user interacts
with. Origins of online contents: This is the original "real-world" sources for the
online information.
©Navid Nikaein 2011 9
Simple Example
V ={1,2,3,4,5,6}
E={{1,2},{1,5},{2,3},{2,5},{3,4},{4,5},{4,6}}
©Navid Nikaein 2011 - p 12
What is a Graph?
Mathematical structure used to model relations between objects
Each graph G(V,E) is pair consisting of a set of nodes/vertices : V(G) a set of links/edges that connect pairs of nodes E(G)
Graph representation : Drawing: several ways to draw a given graph Data structure
List : used mainly for sparse graph Matrix : used mainly for dense graph
©Navid Nikaein 2011 - p 13
Communication network
The infrastructure that allows two or more nodes to communicate with each other Requires a set of standard communication rules, called
protocol, to exchange information over the common medium PDU and SDU format Interfaces
Generally divided into three planes Control plane Data plane Management plane
©Navid Nikaein 2011 14
Network design
• Iterative process of defining the architecture, components, modules, interfaces, and data for a network to satisfy specified requirements
– Topological design – Network architecture and services
• Includes physical, datalink, network, and transport layer – Network realization
• But what are those requirements in MANET?
• How they influence protocol design ?
©Navid Nikaein 2011 15
Network design requirements
• Applications and environments – e.g. commercial or emergency, wired or wireless, indoor, urban, rural
• User requirements and groups – e.g. user organization and priority, civilian or governmental
• Reference scenarios and services – e.g. concentration or random, rich multimedia application
• Technical goals and trade-offs – e.g. scalability, reliable, reconfigurable, rapidly deployable, security performance
• Internetworking – e.g. internet connection
• Network traffics (flow, load, behavior, and QoS) – e.g. interactive real-time, quality-of-service,
– Medium – E.g. wireless, underwater, cable
©Navid Nikaein 2011 16
Network Architecture
• Network Architecture: – Layered: separate communication task, triggers – Cross-layer: information sharing, joint deign, interactions – Integrated : unique communication task – Service oriented: connectivity, mediation, and application services
• Issues: compatibility, interactions, configuration • Example: OSI • Impact:
– Complexity – Performance – Resources – Upgradeability – Interoperability – Standardization
©Navid Nikaein 2011 18
Transport Layer
• Unit: segment/datagram
• Example of Services: • Connection(less)-oriented, same-order delivery • Reliable data, flow control, error control, congestion avoidance,
reservation • (De)Fragmentation, byte-orientation, port numbering • Authentication, E2E encryption
• Example of protocol: TCP, UDP, RTP
• Impact: – Performance(delay, throughput, loss rate) – Fairness – Recovery latency
©Navid Nikaein 2011 19
Network Layer
• Unit: Packet
• Example of Services: • Connection(less)-oriented, routing/forwarding • Fragmentation, host address, metric • mobility management, QoS, error control, security, internetworking
• Example: OSPF, RIP, AODV
• Impact: – Performance – Scalability – Load distribution and congestion – Resource consumption
©Navid Nikaein 2011 20
Data link layer
• Unit: frame • Example of LLC services :
• Reliable transmission, link management, resource control, fragmentation, address resolution, error control, flow control,
• Header compression, ciphering • Example of MAC services:
• Channel access, resource allocation, feedback/measurement mechanisms, QoS support, MAC address
• Example: ATM, Ethernet, PPP, 802.11/16 • Impact:
– Performance (delay and throughput, loss rate ) – Fairness – Resource consumption – Scalability
©Navid Nikaein 2011 21
Physical Layer-Base Band
Unit: bit Medium, frequency, bandwidth, energy
Example of Services: Synchronization, randomizer, inter-leaver, encoder, modulator, flow
control, Equalizer, shape filter, waveform
Example: WiFi, WiMax, LTE Impact:
Bit rate Bit error rate Physical topology Serial or parallel communication Duplex transmission mode Security
©Navid Nikaein 2011 22
Physical Layer – RF Subsystem
Unit : signal Medium, frequency, bandwidth, energy
Example of Services: ADDC, filter, AGC, (de)modulator, (de)coding, power
amplifier, waveform
Impact: Interference Receive signal level BER
©Navid Nikaein 2011 23
Antenna
Unit: Signal Example of Services: Transmit and received electromagnetic waves (convert to current
and vice versa) Omni-directional, directional, switched lobe, dynamically phased
array, adaptive array, MIMO, DAS Metric: EIRP (effective isotropic radiated power)
Examples: dipole, yagi-uda, horn Impact: Transmit power Capacity Spatial (freq) reuse Range vs. interference
©Navid Nikaein 2011 24
Hardware
Unit: IC/Gates (AND and XOR), clock Example of Services: Speed, power consumption, processing, interface Hard chipset, soft chipset, full costume
Example: x86PC, ASIC, adaptive ASIC, FPGA, design-specific FPGA
Impact: Cost Size Performance Power consumption Flexibility Usage
©Navid Nikaein 2011 25
Hardware cont’d
• Form factor – Layout: board size, mounting, connector, height – Examples: ATX, EATX, EmbATX, ITX, PC/104 – Impact:
• Cost • Power supply • System resources • Category of applications • Hardware architecture • Ports and interfaces
©Navid Nikaein 2011 26
Mobile Advanced Networks
Mobile Ad Hoc Networks: MANET
Wireless Mesh Networks: WMN
Wireless (Multimedia) Sensor Networks and Machine to Machine Communication: WSN, WMSN, M2M, IoT
Vehicular Ad Hoc networks: VANET
Delay-tolerant networks : DTN
Cognitive Radio Ad Hoc networks : CRAHN
©Navid Nikaein 2011 28
Original Motivation of MANET
Military needs for battlefield survivability [leiner87] No restrictions imposed by a fixed platform The military cannot rely on access to a fixed, pre-placed
communication infrastructure in battlefield environment Unavailable or unreliable of access due to the destruction of the local
infrastructure or eavesdropping of the information Lack of terrestrial communication infrastructure
Packet Radio Networks Term invented by US military research @ 70 First cellular networks 1G was launched in Japon @79 Second cellular networks 2G GSM was launched in Europe
@82
©Navid Nikaein 2011 29
Complexity of Packet Radio Networks
©Navid Nikaein 2011 - p 30
Highly Dynamic Network
Requires rapid response to
topology changes
Many updates generated by typical routing
algorithms
Requires multiple algorithms at different time
scales
Interest in efficiency
Use of multiple routing algorithms
Relatively scarce radio spectrum
Relatively low bandwidth
Shared Channel
Access to “overheard” information
Control over transmission parameters
Use of integrated algorithms which can be complex and may violate layering
Definition
A collection of nodes forming one or potentially several dynamic autonomous networks Nodes may be mobile or fixed Nodes communicate
using wireless medium without necessarily the intervention of any fixed infrastructure, i.e.
AP/BS Multi-hop fashion (store-and-forward), i.e. transmit range
Nodes acts as a host, and may act as a router
Packet Radio – Multihop - MANET
©Navid Nikaein 2011 31
Backbone
MANET Characteristics
Multihop forwarding Network disconnection
due to Node mobility Traffic load (congestion) Lack of resource Transmission range Obstacle
Render route changes
©Navid Nikaein 2011 32
RAN RAN
MANET Characteristics Cont’d
Wireless Medium Broadcast nature of the medium May render collision and contention
Node Mobility Time-varying topology and resources May render a link failure
Self-Organized Lack of infrastructure May render a (quasi-) distributed operation
Small Devices Limited resources May render Multihop operation
©Navid Nikaein 2011 33
Wireless Network Models
©Navid Nikaein 2011 34
Backbone Network
Single-hop network model e.g. Cellular
Network
Obstacle
Multi-hop network model
e.g. ad hoc networks
Backbone Network Hybrid ad hoc
network model e.g. sensor
network
Architectural Convergence ?
©Navid Nikaein 2011
2G - GSM
2.5 G - EDGE/GPRS
3G - UMTS(WCDMA/HSPA)
4G – LTE/LTE-A Source: J. Erfanian & LOLA Project
- p 35
Network Protocol Convergence
©Navid Nikaein 2011
- Evolution from separate packet-switched and circuit-switched core sub-domains to one common IP core - New IP-based flat mobile core introduced in LTE: Toward ALL-IP-Architecture
Source: ALU
- p 36
Example of MANET Connectivity Graph
Does this graph correctly represents MANET topology?
©Navid Nikaein 2011 37
S D
End-to-end path
Example of MANET Connectivity Graph
©Navid Nikaein 2011 38
S D
End-to-end path S
DX X path
disruption!
time Space-time path Conceptual Graph over time and space
aggregate
Source: T. Spyropoulos
Applications of Ad Hoc Networks [chlamtek,hoebeke] Tactical networks
Military communication and operations
Public safety networks Rescue operation, disaster recovery (firefighters, police, doctors)
Commercial and civilian services Vehicular services such as road, weather, and accident information, inter-vehicle
communication Spontaneous network for group collaboration Sport stadiums, trade-fairs, and shopping mall
Home, office, and university networking Smart Home, Conference, meeting room, virtual classroom
Entertainments Multiuser game, wireless P2P networking, Robotic pets
Sensor Networks Intelligent environments Body area networks Data tracking of environment conditions (weather, earthquake, bridge)
©Navid Nikaein 2011 39
Wireless Technology: Range vs. data rate
©Navid Nikaein 2011 - p 42
Data Rate (Mbps)
Ra
ng
e
ZigBee 802.15.4 802.15.3
802.15.3a 802.15.3c
WPAN
WLAN
WMAN
WWAN
WiFi 802.11
0.01 0.1 1 10 100 1000
Bluetooth 802.15.1
802.22
LTE / WiMax 802.16 HSPA
802.20
NFC
Wireless Mesh Network
©Navid Nikaein 2011 44
Routers
Gateways
Printers, servers
Mobile clients
Stationary clients
Intra-mesh wireless links
Stationary client access
Mobile client access
Internet access links
Node Types Link Types
• Extend the coverage • Transit networks • Do not originate and/or terminate data flows
Access link Backbone links Backhaul links
How it Works : Data flows
©Navid Nikaein 2011 45
User to internet and User to user traffic
Wireless Mesh Networks
Can you think of any application?
©Navid Nikaein 2011 46
Source: I. Akyldiz
Wireless Mesh Networks
©Navid Nikaein 2011 - p 48
Law Enforcement
Intelligent Transport System
Wireless Mesh Networks
©Navid Nikaein 2011 49
Rapidly Deployable Public Safety Network
Comparison
Mobile Ad Hoc Networks
Multihop
Nodes are wireless, possibly mobile
Nodes have the same capabilities/responsibilities
It does not rely on infrastructure
Most traffic is user-to-user
Wireless Mesh Networks Multihop
Nodes are wireless, some mobile, some fixed
Nodes can be routers, gateway, or users
It relies on infrastructure
Most traffic is user-to-gateway
©Navid Nikaein 2011 51
Companies
Aerial Broadband
BelAir Networks
Firetide
Intel
Kiyon
LamTech (ex. Radiant)
Locust World
Mesh Dynamics
Microsoft
Motorola (ex. Mesh Networks)
Nokia Rooftop
Nortel Networks
Packet Hop
Ricochet Networks
SkyPilot Networks
Strix Systems
Telabria
Tropos Networks
52 ©Navid Nikaein 2011
Recent Mesh Products
53
Motorola: IAP4300 – Intelligent Access Point for
MOTOMESH Duo Motorola: MESH Wireless Video Camera
Tropos 5320 Outdoor MetroMesh Router
Mekari MR58 PacketHop Mesh Exchange
©Navid Nikaein 2011
54
IEEE 802.11s
IEEE 802.15.1,2.3
IEEE 802.15.4
IEEE 802.15.5
IEEE 802.16a
Proprietary
Wireless Mesh Standards
©Navid Nikaein 2011
Wireless Sensor Networks
Need to monitor and measure various physical phenomena: Temperature, fluid levels, vibration, strain, humidity, acidity,
pumps, generators to manufacturing lines, aviation, building maintenance, vehicular movement, lightning condition, pressure, noise levels, presence or absence of certain types of objects, mechanical stress levels on attached objects, current characteristics (speed, direction, size) of an object, etc.
Common to many areas including structural engineering, agriculture and forestry, healthcare, logistics and transportation, and military applications.
©Navid Nikaein 2011 56
Wireless Sensor Networks
Connected sensing device that are capable of retrieving data and potentially interacting with the environment
Why Inexistent of wired infrastructure for instance in a remote and/or
hostile environment Cost reduction for installing, terminating, testing, maintaining,
trouble-shooting, and upgrading
Challenge Self-organize networking Energy efficiency Variable channel capacity In-network processing QoS support
©Navid Nikaein 2011 - p 57
Data Aggregation
The process of Aggregating the data from multiple sensors Eliminate redundant transmission Fuse information at intermediate nodes Transmit the processed data to the sink, e.g. base station
©Navid Nikaein 2011 - p 59
Type of Sensors
Passive, omnidirectional sensors Measure a physical quantity at the point of the sensor node Examples: thermometer, light sensors, vibration, microphones, humidity,
mechanical stress or tension in materials, smoke detectors
Passive, narrow-beam sensors Well-defined direction of measurement Examples: camera which can “take measurements” in a given direction,
but has to be rotated if need be
Active sensors actively probes the environment, for example, a sonar of some types of
seismic sensors, which generate shock waves by small explosions
Actuation capable Receive commands and perform a predefined operation
©Navid Nikaein 2011 - p 60
View of a Sensor
Sensing unit sensors and ADC
Processing unit (CPU) Communication subsystem: composed of transceiver and
interfaces the devices with n/w
Coordination subsystem co-ordinates different n/w
devices
A storage unit (memory) Optional mobility/ actuation
unit
©Navid Nikaein 2011 - p 61
Wireless Sensor Networks
©Navid Nikaein 2011 62
• Can you think of any application?
Wireless Sensor Networks
©Navid Nikaein 2011 63
Power Processor
Radio
Sensors Memory
Source: ETH-DCG
Wireless Sensor Networks
Habitat monitoring – Great Duck Island Gather temp, IR, humidity, and other readings from bird nests
on island Determining occupancy of nests to understand breeding &
migration behavior Live readings at http://www.greatduckisland.net
©Navid Nikaein 2011 64
Wireless Sensor Networks
Health Applications Telemonitoring of human physiological data, tracking and
monitoring patients and doctors inside a hospital, and assistance of the elderly
Wearable and implantable sensors can monitor a broad variety of conditions of the patients continuously at all times
Pre-hospital, in-hospital, and ambulatory monitoring possible
©Navid Nikaein 2011 - p 65
Wireless Multimedia Networks
©Navid Nikaein 2011 - p 66
Multimedia surveillance Networks
Health Care delivery Systems
Industrial Process Control
Environmental Monitoring control Systems Traffic monitoring systems
Evolution toward IoT
Smart interconnected sensing objects embedding pervasive information processing connectivity medium Service enabler
Evolution towards “Internet of Things” RFID/tags WSN/WMSN M2M IoT
©Navid Nikaein 2011 - p 67
RFID
WSN M2M
IoT
Machine To Machine Communication
Essentially add intelligent to wireless multimedia sensors and connect devices and remote system Communicating object and Internet of things (IoT)
©Navid Nikaein 2011 - p 68
Toward Smart City
©Navid Nikaein 2011 - p 69
Smart Elec. Smart Water
Appliances
Temperature
Light
Wind Turbine
Solar Panel
Smart Gas
Meters Coms
Home displays TV, Computer
In-Home Energy Display
Breaker Valves
Gateway
Data Center
Wan Communication
Source: ETSI
Comparison
Wireless Mesh Networks
Bandwidth is generous (>1Mbps)
Some nodes mobile, some fixed
Normally not energy limited
Resources are not an issue
Most traffic is user-to-gateway
Wireless Sensor Networks
Bandwidth is limited (tens of kbps)
In most applications, fixed nodes
Energy efficiency is an issue
Resource constrained
Most traffic is user-to-gateway
©Navid Nikaein 2011 70
Motivation
In 2004, the European Commission triggered a socio-economic study (SeiSS) on the impact of intelligent vehicular systems: 5 to 15% reduction in fatalities 10 % to 20% reduction in traffic congestion 40% stand-still reduction with dynamic and real time traffic management …
According to the American Automotive Association study, the cost for the US economy of traffic accident is 160 billion $ yearly Approx $1000 per citizen per year
There is a clear benefit to make cars able to talk and exchange data ! A large set of applications have been defined and are ranked in three classes
Traffic safety Accident avoidance Traffic Efficiency
Congestion avoidance Real-time optimal path
Infotainment Internet access, advertisement and P2P
©Navid Nikaein 2011 - p 72
Source: J. Harri
Vehicular Ad Hoc Networks
Dedicated interconnection of cars to form a network Supporting connection to roadsides and existing wireless
infrastructures
©Navid Nikaein 2011 73
Source: J.-C. Kao
Vehicular Ad Hoc Networks
©Navid Nikaein 2011 74
Reduce CRASHES
Increase
Automation?
- Automatic Driver Assistance? - Emergency Vehicle Warning
- Inter-Vehicle warning
Minimize effects
of Driver Error
- Intersection collision avoidance
- Curve speed Deceleration
Improve Driver
Situational Awareness
Safer Roads Source: F. Kargl
Vehicular Ad Hoc Networks
©Navid Nikaein 2011 75
Reduce CONGESTION
Improve Traffic
Information
Improve Situational
Roadway Awareness
- Real time traffic information
- Alternative route guidance
- Dynamic roadway condition info.
- Emergency situation management
Manage Traffic
Flow?
- Dynamic flow control?
- Dynamic roadway pricing?
More Efficient Driving Source: F. Kargl
Application Ranking
Active safety Accident avoidance Cooperative emergency applications
Real-time traffic control and monitoring Vehicular traffic monitoring and congestion avoidance Optimal path computation
Infotainment Cooperative files download (cartorrent) and Internet access
Parking assistance: Find a park place easily in a city Air pollution emission measurement and reduction Law enforcement Internet access in cars
©Navid Nikaein 2011 - p 77
Communication Paradigm
I: infrastructure: in general fixed (WiFi/WAVE APs) but it can be mobile (specific police cars)
V: Vehicle: in general cars but it can be trucks, busses, trains, etc.
©Navid Nikaein 2011 - p 78
V2I: Vehicle to Infrastructure
V2V: Vehicle to Vehicle
V2V2I: Vehicle to Vehicle to Infrastructure
I2V : Infrastructure to Vehicle
I2V2V: Infrastructure to vehicle to vehicle
I2V2I ?
In-vehicle communication
VANET Requirements
©Navid Nikaein 2011 - p 79
WLAN has been designed to provide Internet-grade communication ITS Communications have different requirements
But they are investigated as if similar !
Internet Communication Traffic Safety
Mostly Unicast
Bursty Traffic
Throughput Oriented
Delay ‘tolerant’
Large-scale
Mostly Broadcast
Mostly Periodic Traffic
Message Oriented
Delay Centric
Local Scale
Heterogeneous Vehicular Networks
©Navid Nikaein 2011 80
Always Best Connected/Served? May involve lots of technologies ?
Source: F. Kargl
Heterogeneous Vehicular Networks
From Vehicular Ad Hoc Networks (VANET) Dedicated interconnection of cars to and form a network Supporting connection to roadside infrastructure
To Heterogeneous Vehicular Networks Extension of VANET considering cellular and satellite
networks When dedicated communication cannot be established When multi-hop communication is not possible or efficient
Trade-off between cellular/satellite systems and WLAN in ad hoc mode
©Navid Nikaein 2011 - p 81
Intelligent Vehicle / Transport
©Navid Nikaein 2011 - p 83
Motocycle Warning Emergency Vehicle
Source: BMW F&T & J. Harri
Source:
Vehicular Ad Hoc Networks
How to notify congestion and manage road traffics ? Sensor-based collection: Costly (install everywhere), Centralized Vanet-based collection: The vehicle IS the sensor (CHEAP); Disseminate
traffic data only when/where necessary (SCALABLE)
©Navid Nikaein 2011 84
Source: T. Spyropoulos
Vehicular Ad Hoc Networks
Unlike other adhoc and sensor networks CPU and power are NOT key resources
Bandwidth is the key information network resource Bandwidth and delay guarantees depend on applications’
requirements
Links between peers will be dynamic and unstable Notion of platoons
Move as one simultaneously increase the capacity without additional lanes)
Nodes dynamically leave and join platoons
Links with fixed and mobile (enhanced probe vehicles) Mobility is constrained and directional
©Navid Nikaein 2011 86
Delay-Tolerant Networks
There is no direct path from node S to node D at any given time.
Packets from node S can be delivered to node D if intermediate nodes can hold/carry the packets. At 8:00 am, node S sends the packets to node 2; at 10:00am node 2 forwards the packets to node 3; and at 11:30 am node 3 forwards the packets to node D.
88 ©Navid Nikaein 2011
Delay-Tolerant Networks Intermittent link (dis)connection No guarantees on End-to-End path Predictable / Opportunistic disconnection Opposed to assumptions in today’s Internet always connected, low round trip time, etc.
89
A B
E
D
F
C
©Navid Nikaein 2011
Delay-Tolerant Networks
Intermittent link (dis)connection High latency : signal propagation and/or intermittent connectivity Low data rate Long queuing times Lack of resource at end nodes
Opposed to the assumptions of the Internet today always connected, low round trip time, etc.
©Navid Nikaein 2011 90
S D
End-to-end path S
DX X path
disruption!
Terminology for DTNs
There are many different terminologies used for DTNs in the literature, such as eventual connectivity space-time routing partially connected transient connection opportunistic networking extreme networks delay-tolerant network disruption-tolerant networks Sparse networks
91 ©Navid Nikaein 2011
Delay-Tolerant Networks
©Navid Nikaein 2011 92
time (days)
Connectivity: Village – City band
wid
th bike
satellite phone
Connection Availability BW Delay cost Satellite 3-4 times per day Low Msec High Bike Once per day High Hours Medium phone On demand Medium Msec High(day)
Low(night)
Delay-Tolerant Networks
Location-dependent Services Current events within 1km of where I am? Any media? Any good Asian restaurants around with a wait less than 15min? Anybody nearby with tickets to sell for today’s Real Madrid game?
Social Networking Services Are any of my friends (e.g. from Facebook) nearby, in the same bar/train? Who else is on this train, and what are their profiles?
Extending the realm of Existing ones File-sharing, downloading popular content, cached web access
Power constrained networks
Why not using the existing applications, e.g. iPhone apps? Note: Not a replacement of the existing infrastructure
©Navid Nikaein 2011 94
Source: T. Spyropoulos
Cognitive Radio Ad Hoc Networks
CR is a radio that can tune its radio based on the interaction with its environment Learn and adapt Reconfigurability : SDR concept
Spectrum-aware communication Limited available radio spectrum Inefficiency spectrum usage
Goal is to find the best available spectrum holes Requires cooperation among systems and networks
Spectrum sensing: detect spectrum opportunities Spectrum management: analysis and decision Spectrum mobility: switch the frequency of operation Spectrum sharing: cooperation with license user
©Navid Nikaein 2011 96
Simulation Tools for MANET
NS-2/3 http://www.isi.edu/nsnam/ns/ TCL-TK for scenario setup C++ for protocol design
GloMoSim http://pcl.cs.ucla.edu/projects/gl
omosim/ C and parsec (parallel simulation
capability)
Qualnet http://www.scalable-
networks.com/ Commercial version of GloMoSim
Matlab http://www.mathworks.com/
Omnet http://www.omnetpp.org/ C++ for protocol design
GTNET http://www.ece.gatech.edu/rese
arch/labs/MANIACS/GTNetS/ C++
Opnet http://www.opnet.com/solutions
/network_rd/modeler.html C++
Sinalgo http://www.dcg.ethz.ch/projects
/sinalgo/ java
©Navid Nikaein 2011 99
A brief Comparison
Simulation No interaction with the external entities (closed environment) Part or all of the elements of a network/system is modeled or abstracted
Emulation Bring the external elements with their I/O streams (open environment) Decision on which element is real or modeled depends on the use case
and purpose of the experiments At least one thing is modeled
Real testbed All the elements are real Part of the testbed maybe controlled
100
A brief Comparison
Experiment
Scenario Setup
Abstraction / Modeling
Reproducibility
Scalability / Costs
Limitation
Net Traffic & Mobility
Analytical +++ - +++ +++ CPU/ Abstracted/ Modeled
Simulation ++ + +++ ++ Abstraction Modeled
Emulation + ++ ++ ++ CPU/Cost Modeled / Real
Real Testbed - NA - - Cost Real
101
Expectation from the Validation Platforms
Analytical
• UML • FreeMat
• IDL • Matlab • SciLab • Octave
Simulation
• Sinalgo • NetSim
• GloMoSim/Qualnet • NS-3 • Opnet
• Omnet++
Emulation
• NS3 • NistNEt • CORE • USPR2 • WARP
• CMU-DSR • ORBIT • OAI
Real Testbed
• PlanetLab/OneLab • NITOS
• GnuRadio • WARP • ORBIT
• Sundance, BEE2, WiTestLab • USPR2 • OAI
Scalability Reproducibility Applicability
Abstraction Level Realism Level
102
Seven Bridges of Königsberg (Kaliningrad, RU)
Problem is to find a walk through the city that would cross each bridge exactly once
Alternative problem is to find a path that traverses all bridges and also has the same starting and ending point
©Navid Nikaein 2011 - p 105
What matters is the sequence of bridge crossed
Solution exists iff ?
What is a Graph?
Mathematical structure used to model relations between objects
Each graph G(V,E) is pair consisting of a set of nodes/vertices : V(G) a set of links/edges that connect pairs of nodes E(G)
Graph representation : Drawing: several ways to draw a given graph Data structure
List : used mainly for sparse graph Matrix : used mainly for dense graph
©Navid Nikaein 2011 - p 106
Simple Example
V ={1,2,3,4,5,6}
E={{1,2},{1,5},{2,3},{2,5},{3,4},{4,5},{4,6}}
©Navid Nikaein 2011 - p 107
Type of graphs
Undirected graph and directed graph (digraph) Directed graph FSM
Symmetric and asymmetric
Simple graph vs. multigraph (loop and multiple edges)
Weighted graph Such weight may represent cost, length, capacities Examples:
Dijkastra algorithm Minimum cost spanning tree, shortest path maximal flow
Q: Weights are assigned to edges or vertices?
©Navid Nikaein 2011 - p 108
Classes of graphs
K-Regular graph Each vertex has the same k neighbor Example: 0-regular to 3 regular
Complete graph each pair of vertices has an edge connecting them Example: K1 to K5
Connected graph vs. disconnected graph If there is a path between any pair of vertices
K-vertices and k-edges connected graph
©Navid Nikaein 2011 - p 109
Classes of Graph
Bipartite graph The vertices set can be partitioned into two sets
Complete bipartite graph
Path Graph Ordered list of vertices
Cycle Graph Connected 2-regular
©Navid Nikaein 2011 - p 110
Classes of graph
Planner Graph Vertices and edges can be drawn in a plane such that no two
edges intersects, i.e. embedded in the plane Any cycle that surrounds a region without any edges forms a
face
Tree Connected graph with no cycle
Forest Graph with no cycle, distinct union of trees
©Navid Nikaein 2011 - p 111
Subgraphs
A subgraph H of graph G is a graph if V(H) in V(G) and E(H) in E(G) G contains H, and is a supergraph of H
H is a spanning subgraph of graph G if it has the same number of vertex as G. We say that H spans G
H is a k-spanner subgraph of G if any two vertex u,v are at most k times far apart in H than on G K is referred as dilatation number
H is an induced subgraph of graph G if xy is an edge of H iff xy is an edge of G
©Navid Nikaein 2011 - p 112
Walks
Sequence of vertices and edges, where the vertices that precede and follow an edge are the end vertices of that edge Closed walk: first and last vertices are the same opened walk
Path is an opened walk where no edges and vertices are repeated
Length of a walk Number of edges used for a walk
©Navid Nikaein 2011 - p 113
Other Properties
Degree of a vertex V is the number of vertices incident to V Total degree of a graph = 2x|E|, where n is number of edges Degree sequence : list of degrees in non-increasing order Maximum degree: largest degree over all vertices
Adjacency: two vertices u and v are called adjacent if an edge exists between them
Neighborhood: all vertices adjacent to v (induced subgraph of G) Closed: when v is included Opened: when v is not included
distance : the length of a shortest path between any two vertices u, v d= 0 , when u=v d=∞ , when u and v are unreachable Eccentricity of v is the maximum distance from v to any other vertex u
Graph diameter has the maximum eccentricity and graph radius is the minimum
©Navid Nikaein 2011 - p 114
Graph Eccentricity
Eccentricity of node 2 is the maximum distance from node 2 to vertex 3 and 4
Max/Min eccentricity for all nodes give the graph diameter/radius
©Navid Nikaein 2011 - p 115
Dominating sets
Dominating set DS of a graph is a vertex subset whose closed neighborhood includes all vertices of the graph DS is a subset of nodes such that each node is
either in DS or has at least one neighbor in DS
DS can be Weakly connected dominating set WCDS Connected Dominating set CDS Minimum CDS
©Navid Nikaein 2011 - p 116
Independent set
Independent set is a set of vertices of which no pair is adjacent Pair-wise disjoint or mutually nonadjacent
A graph can be decomposed into independent sets in the sense that the entire vertex set of the graph can be partitioned into pair-wise disjoint independent subsets
©Navid Nikaein 2011 - p 117
Problems in graph
Graph coloring/labeling Edge/vertex/face coloring Four-color theorm
Route problems Minimum spanning tree Shortest path Seven bridge of konigsberg Three cottage problem Travelling salesman problem
Network flow Max flow min cut
Visibility graph Museum guard
Covering problem Max clique and independent set
©Navid Nikaein 2011 - p 118