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VANET

VANET. Routing Protocol with prediction based mobility model in V ehicular A d Hoc Net work . Arnab Kumar Banik Department of Electrical Engineering The Pennsylvania State University 23 rd April, 2010. Outline :. Understanding VANET Purpose/Objective Characteristics

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VANET

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  1. VANET Routing Protocol with prediction based mobility model in Vehicular Ad Hoc Network Arnab Kumar Banik Department of Electrical Engineering The Pennsylvania State University 23rd April, 2010

  2. Outline: • Understanding VANET • Purpose/Objective • Characteristics • System Architecture • Related Protocols • Simulation • Evaluation • Conclusions

  3. UNDERSTANDING VANET • VANET:Vehicular Ad Hoc Network is a vehicle -to- vehicle and vehicle -to- roadside wireless communication network • VANET formed with vehicles and roadside beacons where vehicles become mobile nodes that communicate wirelessly without central access point • It is an integration of ad hoc network, WLAN and cellular technology

  4. VANET vs. MANET • Similar to MANET from perspective of node movements • Dissimilar to MANET from the perspective of high rates of nodes’ movement and highly varying channel distributions.

  5. Purpose / Objectives • Two category of Communication services • Safety Applications • Comfort services • Safety Applications: • Provided information / files on • Accident, traffic congestion, Road construction / blockade • Location of nearby gas station / motel / parking places • Sensitivity: • Time sensitive for the message to be relevant / effective • Must target to relevant receivers • Emergency message should have precedence over comfort • Security and confidentiality • Comfort Services: • Internet and multimedia access to co-passengers.

  6. VANET helps in giving early warning to avoid likely accidents

  7. Characteristics: • High Dynamic Topology • Frequent disconnected Network • Uncertainty in mobility modeling • Communication Environment • Hard Delay Constraint • Interaction with onboard sensors

  8. Architecture • Antenna • Modulation • Spectrum allocation • IEEE 802.11p standard • Consist of Five layers • Physical Layer • MAC Layer • Network Layer • Application Layer • Safety Layer • Concentrate on: • Avoiding transmission collision • Achieve reliable medium access • Follow IEEE 802.11p and IEEE 1609.4, RR-ALOHA standard • Routing protocol • Multihop Communication • Redesign existing Unicast, Multicast, Broadcast, Geocast etc to meet VANET characteristics • V2V connectivity • Local RSU connectivity • Internet connectivity • Authentication, Data integrity • Anonymity, Availability • Low Overhead, Privacy, • Real Time constraints MAC: Media Access Control

  9. Routing Protocols: • Principally, operation of VANET and MANET similar except the fact that VANET has high speed of mobility, and varying communication environment • So most routing algorithms are applicable, but it needs to be modified to adapt to changed characteristics of VANET. • Several such algorithms that are upgraded for improved performance are listed below: Ad-hoc Routing: Contd….

  10. Routing Protocols: (contd.)

  11. Example of Different Routing protocol UNICAST Limited to source  Destination BROADCAST Not Limited to source  Destination GEOCAST Limited to a geographical region

  12. SIMULATION

  13. Work Flow Carried out: • Installation of VanetMobisim (in Windows) • Preparing “.xml” file for mobility model generator • Mobility Model trace file generation • Installation of NS-2 (NS-allinone-2.34) on Linux Platform • Generating ‘.tcl’ file for simulation • Using cbrgen.tcl file to include in primary ‘.tcl’ file • Running simulation • Generating NS2 trace file and NAM • Analyzing trace file to study performance

  14. SIMULATION Significance • Evaluation of VANET protocol with large number of nodes is most feasible by computer modeling and simulation as real outdoor experiments will be tedious and expensive. Present SIMULATION plan • In present study, we will work on a VANET simulation using VanetMobiSim / NS-2 application. • In VanetMobiSim, we will use one micro-mobility model belonging to IDM (Intelligent Driver Model) family. • To be specific , we will be using IDM-LC (lane Changing scenario) in mobility model building.

  15. Simulation Architecture • Traffic simulation tool that generates a vehicular mobility traces. • Network simulator that generates the communication environment.

  16. VanetMobiSim Processes: • Input: • Defining xml file with VANET parameters such as nodes, area, speed, Time etc. • Output: • Generate mobility model (Traffic generator) trace file in different output formats such as: • Ns-2 file • QualNet file • GloMoSim file • NET file • Provides visualization of the mobility scenario. • A screen shot of the model in an xfig figure. • In out context we have output it in NS-2 trace file as subsequently we will be using NS-2 for CARLINK (IDM-LC).

  17. Input .xml file Comments need to be removed to extract trace file Sample example .xml files are available in “ ../vanet_sources/ jar” which may be edited suitably to meet the respective objectives) • Command line: (under directory “ ../vanet_sources/ jar”) • % java –jar VanetMobiSim.jar xxx.xml

  18. Output trace.txt file (traffic trace generator) the initial positions subsequent positions of nodes in every time steps

  19. Dumped figures from mobility model generation (several examples as generated) IDM_LC IDM_LC (Intelligent Driver Model – Lane Changing) Nodes: 20 Area: 1000 * 1000 Simulation Time: 200 Time Step: 0.1 Traffic Light: 6 The one we have used in simulation

  20. Dumped figures from mobility model generation (several examples as generated) GDF Geographical Data File IDM_IM (Intelligent Driver Model – Intersection Management) Space-Graph (Random Graph Criteria)

  21. VANET simulator Advantages • Can develop complex vehicular mobility models for the simulations. • The simulations are VANET specific and is open-source application. • It supports both macro-mobility and micro-mobility specifications. • The mobility model may be generated just once and then used for simulating different kind of network configurations. • The output trace file is compatible with NS-2 file format

  22. NS-2 • It is Network Simulator • The package used to simulate behavior of networks and generates trace file to describe • Network Topologies • Log events that happen under any load • Depends on TCL/TK, Otcl, TclCL • It also associates with NAM (Network Animator) • It animates the traces derived from simulation • Analyze events to understand the network behavior • Post Processing: • Analyse trace output with perl, awk, TCL, Matlab, etc

  23. Trace file from VanetMobisim (Traffic/Mobility Model) FLOW-CHART NS Trace File for analysis NS2 Simulation INPUT OUTPUT • NS Simulator Library • Event Scheduler Objects • Network Component Objects NAM File for Network Animation

  24. NS-2 Installation: (in LINUX platform) Download NS-2.34 from the following link; (This also includes installation guidelines http://nsnam.isi.edu/nsnam/index.php/Downloading_and_installing_ns-2 After downloading, copy of ns-allinone-2.34.tar.gz from above link, the following steps executed: % tar -xzf ns-allinone-2.34.tar.gz % cd ns-allinone-2.34 (to make it compatible for ubuntu-9.10 version, some UNIX commands need to be executed as suggested in this link http://lotti.netsons.org/2009/12/install-ns-allinone-2-34-on-ubuntu-9-10/ Then give command: % ./install (under the directory: …/ns-allinone-2.34) Once following message comes: Nam has been installed successfully. Ns-allinone package has been installed successfully. Next step is to link LD_LIBRARY_PATH environment variable by giving following commands: %export LD-LIRARY-PATH=/home/raja/NS2/ ns-allinone-2.34/bin %export LD-LIRARY-PATH=/home/raja/NS2/ ns-allinone-2.34/lib %export TCL-LIRARY=/home/raja/NS2/ ns-allinone-2.34/tcl8.4.11/library Or %setenv LD-LIRARY-PATH /home/raja/NS2/ ns-allinone-2.34/bin %setenv LD-LIRARY-PATH /home/raja/NS2/ ns-allinone-2.34/lib %setenv TCL-LIRARY /home/raja/NS2/ ns-allinone-2.34/tcl8.4.11/library Then give command: % cd ns-2.34 % ./validate This will complete the successful installation.

  25. Running NS-2 simulation • Creating / preparing necessary xxx.tcl file (using tcl and C++ commands) • Then from parent tree you need to go to “bin” directory [ i.e. ../ns-allinone-2.34/bin] • And then prompt the command • % ns xxx.tcl • Next we investigate general parameters in xxx.tcl file.

  26. Input data to NS2 .tcl file Transport Layer (Traffic Agents): TCP, UDP Network Layer (Routing agents): WirelessAODV, DSR, DSDV, etc Interface que: FIFO Que, Droptail Queue, priority Que etc Logic Link control Layer: IEEE 802.2; ARP set opt(chan) Channel/WirelessChannel set opt(prop) Propagation/TwoRayGround #set opt(netif) NetIf/SharedMedia set opt(netif) Phy/WirelessPhy #set opt(mac) Mac/802_11 set opt(mac) Mac/802_11 #set opt(ifq) Queue/DropTail/PriQueue ;# for dsdv set opt(ifq) CMUPriQueue ;# for dsr set opt(ll) LL set opt(ant) Antenna/OmniAntenna set opt(x) 670 ;# X dimension of the topography set opt(y) 670 # Y dimension of the topography set opt(cp) “home/raja/NS2/ns-allinone-2.34/bin/cbr-20-test" set opt(sc) “home/raja/NS2/ns-allinone-2.34/bin/ns_trace.txt" set opt(ifqlen) 50 ;# max packet in ifq set opt(nn) 20 ;# number of nodes set opt(seed) 0.0 set opt(stop) 1000.0 ;# simulation time set opt(tr) out.tr ;# trace file set opt(rp) dsr ;# routing protocol script (dsr or dsdv) set opt(lm) "off“ ;# log movement To generate cbr file # ns cbrgen.tcl –type cbr –nn 20 -seed 1.0 –mc 14 –rate 4.0 >cbr-20-rest

  27. Trace Format Example The sample NS-2 trace file and their format is as described below (Hex)

  28. NS-2 Trace File Analysis: • On simulation, NS-2 will generate a trace file and optionally a nam file • A trace file now need to be analyzed in a manner to describe the performance of the mobility model • Traces: They record each individual packets as it arrives, departs or is dropped at a link or queue • Monitors: They record counts of various interesting quantities such as packet and byte arrivals, departures etc. • The NAM file will provide the network animation.

  29. Display of Network Animation (NAM) at different time Time: 26.388472 ms Time: 37.239150 ms  • Displayed the nodes within network link at a particular time • Also to note the shifting of node positions with time  Time: 86.219473 ms Time: 123.809964 ms 

  30. Extracting Information (volume of packets by diff nodes) • Mostly awk, tcl, matlab are used to extract information to display • The following ‘awk’ script used to estimate throughput against different nodes. (say script file: file3.awk) • BEGIN { sim_end=200; • i=0; • while (i<=sim_end) {sec[i]=0; i+=1;}; • } • { if ($1=="r" && $7=="cbr" && $3=="_2_") { • sec[int($2)] += $8; • }; • } •  END {i=0; • while(i<=sim_end) { • print i " " sec[i]*8; • i+=1 • }; • } • Then invoking command: awk –f file3.awk IM.tr >out3.xgr • It creates file (x,y) with time and throughput for node no 3. • Similar file can be prepared for different nodes.

  31. Displaying Results • The following command use to display plot in ‘xgraph’ • % xgraph out2.xgr out3.xgr out4.xgr out5.xgr out6.xgr out7.xgr out8.xgr out9.xgr & • Provided plots of nodes 2 -9 in xgraph as below. • It shows main congestion time window when packets are received Throughput  (Congestion Window) Time 

  32. Result Discussions: Throughput (Congestion window) bit/sec vs. Time • Throughput (bits/s) for Nodes 2,6 and 9 • Indicates the amount (size) of packet received at different time. • Throughput (bits/s) for Nodes 14,18 and 22 • Indicates the amount (size) of packet received at different time.

  33. Throughputs (bits/sec) of • all nodes over Time • selected range of nodes over time The middle nodes found to receive more packets over entire period

  34. File: pdr.awk Packet Delivery Ratio BEGIN { nSentPackets = 0 ; nReceivedPackets = 0 ; rTotalDelay=0.0 ; } { strEvent = $1 ; rtime = $2 ; strAgt = $4; idPacket = $6 ; strType = $7 ; if (strAgt == "AGT" && strType =="cbr") { if (strEvent == "s") { nSentPackets += 1; rSentTime[ idPacket ] = rTime; } if (strEvent == "r") { nReceivedPackets += 1; rReceivedTime[ idPacket ] = rTime; rTotalDelay += rReceivedTime[ idPacket] - rSentTime[ idPacket ]; } } } END { rTime = rEndTime - rStartTime ; rPacketDeliveryRatio = nReceivedPackets / nSentPackets * 100; printf( "PacketDeliveryRatio: %10.2f\n", rPacketDeliveryRatio ); } • It is the amount (total size) of packet received to the amount of packets sent by all nodes. • The estimation is made by using UNIX ‘awk’ script (given in the right side) • The overall Packet Delivery Ratio is estimated to be 59.89% Command line: # awk pdr.awk out.tr >pdr.txt #cat pdr.txt

  35. Conclusions • VANET relates to vehicle to vehicle and vehicle -to- roadside wireless communication network • It has twin objectives of safety and comfort services. • VANET is different from MANET because of its high dynamic topology and highly varying channel distribution. • This makes most existing routing protocol not suitable for VANET as it resulted in frequent link failure. • Several upgradation of existing routing protocols has showed improved performance in VANET • VanetMobiSim that provides both macro-mobility and micro-mobility descriptions and NS-2 used for our simulation. • A packet delivery ratio of 59.9% achieved using 20 nodes and DSR routing protocol. Which suggest that conventional algorithms (of MANET) are not most suitable for VANET • Simulation using PR-AODV, COIN, GPRC, A-STAR etc (as carried out by various authors) have established improvements over DSR / AODV etc

  36. Links /References • Tcl/Tk – http://www.tcl.tk/software/tcltk/ • Nsnam web pages – http://www.isi.edu/nsnam/ • NS by example – http://nile.wpi.edu/NS/ • Tutorial – Marc Greis's tutorial • Discrete-event simulation software – http://www.topology.org/soft/sim.html • http://mobnet.epfl.ch/2009/hoe/HoE-ns2-Mobnet09.pdf • Yue Liu, Jun Bi, Ju Yang; “Research on Vehicular Ad Hoc Networks”; Chinese Control and Decision Conference (CCDC), 2009. Page(s): 4430 – 4435. • Fan Li and Yu Wang; “Routing in Vehicular Ad Hoc Networks: A Survey”, IEEE Vehicular Technology Magazine, Volume 2, Issue 2, June 2007; Pages: 12-22. • VinodNamboodiri and LixinGao; “Prediction-Based Routing for Vehicular Ad Hoc Networks”, IEEE Transactions on Vehicular Technology, Vol. 56, No. 4, July 2007; Pages: 2332-2345.

  37. THANK YOU

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