"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