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Alexander Afanasyev

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Content Distribution in VANETs using Network Coding: Evaluation of the Generation Selection Algorithms Alexander Afanasyev Tutors: Seung-Hoon Lee, Uichin Lee – PowerPoint PPT presentation

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Title: Alexander Afanasyev


1
Content Distribution in VANETs using Network
Coding Evaluation of the Generation Selection
Algorithms
  • Alexander Afanasyev
  • Tutors Seung-Hoon Lee, Uichin Lee

March 2, 2009
2
Content Distribution in Vehicular Ad-Hoc
Networks (VANETs)
  • Applications
  • Software updates and patches (e.g., navigation
    map, games)
  • Multimedia data downloads (e.g., videos, news,
    etc.)

3
Content Distribution Challenges
  • High mobility (i.e., highly dynamic networks)
  • Error-prone channel (due to obstacles, multi-path
    fading, etc.)

4
CarTorrent BitTorrent-like Cooperative Content
Distribution in VANETs
A file is divided into pieces
Web Server
Exchange pieces via Vehicle-to-Vehicle
Communications
Download a file (piece by piece)
Not useful!
  • Problem Peer Piece selection ? coupon
    collection problem

Cannot complete download!
5
Using Network Coding CodeTorrent
A file is divided into pieces
Web Server
Any linearly independent coded packet is helpful
  • Network coding effectively mitigates the
    peer/piece selection problem and improves the
    performance!

6
Network Coding ProblemProcessing Overhead
Single Generation
Overhead
5/10/50 Generations
  • Delay without O/H
  • Small of generations is a better choice
  • Larger of generations ? more severe coupon
    collection problem

7
Mitigating Coding Overheads
  • Solution divide a file into small generations
  • Problem too many generation causes a coupon
    collection problem
  • Conflicting goals maximizing benefits of NC vs.
    minimizing coding O/H

50MB
8
Mitigating Coding Overheads
  • Solution divide a file into small generations
  • Problem too many generation causes a coupon
    collection problem
  • Conflicting goals maximizing benefits of NC vs.
    minimizing coding O/H

10MB x 5
9
What is optimal strategy for generation
downloading?
Gen1
Gen2
Gen3
Global (neighbor status)
Request to ??
Gen1
Gen2
Gen3
Local (my status)
  • Checking neighbor rank improve chances of
    linearly independent block, but
  • Low-rank cars can also have valuable blocks
  • Back to the BitTorrent problem of
    piece/generation selection
  • Local status based decision (i.e., the least/the
    most downloaded generation, sequential order)?
  • Neighbor status based decision?
  • Random?

10
Generation Selection Strategies
Virtual Global Completeness Vector
Global Min Gen 4 Global Max Gen 3 Random
Random Sequential Gen 1
11
Simulation Setup
  • Communications
  • 802.11b 11Mbps Two-ray ground propagation
  • Mobility
  • Random Waypoint model w/ speed range of 0,20
    m/s
  • Westwood area map 2400m2400m
  • Nodes
  • 3 APs file sources
  • 200 nodes/40 interest level
  • 80 nodes are downloading a file
  • Download parameters
  • 50 megabyte file
  • 10 generations

Westwood area map
12
Downloading all generations in parallelGeneration
Progress
Global Min
Local Min
Random
Neighbor Min
13
Downloading all generations in parallelOverall
Progress
Neighbor-aware strategy improves at the beginning
of downloading
Local-aware and random strategies has smaller tail
confidence interval is calculated with
probability 95 using 8 simulations
14
Downloading all generations in parallelFinishing
times histogram
  • Conclusions
  • Network-aware strategy has long tail of finishing
    times
  • Local and random strategies behave almost as good
    as global status-aware

15
Downloading generations (semi-)sequentiallyGenera
tion Progress
Global Max
Local Max
Neighbor Max
Sequential
16
Downloading generations (semi-)sequentiallyOveral
l Progress
!!! Neighbor-aware strategy outperforms local and
global one
confidence interval is calculated with
probability 95 using 8 simulations
17
Downloading generations (semi-)sequentially Finish
ing times histogram
  • Conclusions
  • Network-aware strategy outperforms other
    strategies
  • Average finishing time for global/local max
    strategies 1.5 times worse than neighborhood
    status aware policy

18
Parallel vs Sequential DownloadingOverall
progress of the best strategies
  • Conclusions
  • Neighbor-aware generation choosing considerably
    improves chances for helpful block (linearly
    independent) at the beginning
  • Local or random strategy improves download
    finishing time

19
Parallel vs Sequential DownloadingFinishing
times histogram
  • Conclusions
  • Neighbor-aware strategies have on average 20
    worse finishing times than local max strategy

20
Interesting Facts
Rank checking
  • Checking generation rank of the available
    generation greatly improves performance for
    neighbor status aware strategies
  • Integer vector gossiping decrease overall
    download performance

No rank check
Bool vector
Int vector
21
Conclusion
  • Generation selection strategy in multi-generation
    CodeTorrent downloads have big impact on the
    overall download performance
  • Local status aware strategies (local-min, random)
    have the best finishing performance
  • Neighbor status aware strategies have the best
    start-up performance
  • It is important to check rank for neighbor status
    aware strategies
  • Future work
  • Investigate performance of combined strategies
  • Check performance using different node mobility
    models
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