Content Distribution in VANETs using Network Coding: The Effect of ... - PowerPoint

							 Content Distribution in VANETs using Network Coding:
 Evaluation of the Generation Selection
 Algorithms


                       Alexander Afanasyev

                Tutors: Seung-Hoon Lee, Uichin Lee




March 2, 2009
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.)
Content Distribution Challenges

  ◦ High mobility (i.e., highly dynamic networks)
  ◦ Error-prone channel (due to obstacles, multi-path fading, etc.)
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!
Using Network Coding: CodeTorrent

              A file is divided into pieces
     Web
     Server




                                                                                       1 more?


                                              Any linearly independent coded packet is helpful


 
 Network Coding Problem
 Processing 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
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
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




                         1           4
What is optimal strategy for
generation downloading?
                                Global:             Gen1   Gen2   Gen3
                                (neighbor status)

               Request to ??

                                Local:              Gen1   Gen2   Gen3
                                (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?
Generation Selection Strategies




                                   Virtual “Global”
                                 Completeness Vector

             Global Min: Gen 4
             Global Max: Gen 3
             Random: Random
             Sequential: Gen 1
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: 2400m*2400m
   Nodes                                  Westwood area map
    ◦ 3 APs: file sources
    ◦ 200 nodes/40% interest level:
      80 nodes are downloading a file
   Download parameters
    ◦ 50 megabyte file
    ◦ 10 generations
Downloading all generations in parallel
Generation Progress




            Global Min              Local Min




          Neighbor Min               Random
      Downloading all generations in parallel
      Overall 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
  Downloading all generations in parallel
  Finishing times histogram




Conclusions:
 Network-aware strategy has long tail of finishing times

 Local and random strategies behave almost as good as global status-aware
  Downloading generations (semi-)sequentially
  Generation Progress




 Global Max                Local Max




Neighbor Max               Sequential
      Downloading generations (semi-)sequentially
      Overall Progress




                                                                                !!! Neighbor-aware
                                                                               strategy outperforms
                                                                               local and global one




* confidence interval is calculated with probability 95% using 8 simulations
  Downloading generations (semi-)sequentially
  Finishing 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
  Parallel vs Sequential Downloading
  Overall 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
  Parallel vs Sequential Downloading
  Finishing times histogram




Conclusions:
 Neighbor-aware strategies have on average 20% worse finishing times than
  local max strategy
Interesting Facts
                                     Rank
   Checking generation rank of    checking
    the available generation
    greatly improves performance
    for neighbor status aware                   No rank
    strategies                                   check




   Integer vector gossiping            Bool
    decrease overall download          vector
    performance
                                                  Int
                                                vector
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