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CodeTorrent: Content Distribution using Network Coding in VANET Uichin Lee, JoonSang Park, Joseph Yeh, Giovanni Pau, Mario Gerla Computer Science Dept,

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Presentation on theme: "CodeTorrent: Content Distribution using Network Coding in VANET Uichin Lee, JoonSang Park, Joseph Yeh, Giovanni Pau, Mario Gerla Computer Science Dept,"— Presentation transcript:

1 CodeTorrent: Content Distribution using Network Coding in VANET Uichin Lee, JoonSang Park, Joseph Yeh, Giovanni Pau, Mario Gerla Computer Science Dept, UCLA

2 2 Content Distribution in VANET  Multimedia-based proximity marketing: Virtual tours of hotel rooms Movie trailers in nearby theaters  Vehicular ad hoc networks (VANET): Error-prone channel Dense, but intermittent connectivity High, but restricted mobility patterns No guaranteed cooperativeness (only, users of the same interests will cooperate)  How do we efficiently distribute content in VANET? Traditional approach: BitTorrent-like file swarming

3 3 BitTorrnet-like File Swarming  A file is divided into equal sized blocks  Cooperative (parallel) downloading among peers From Wikipedia

4 4 Swarming Limitation: Missing Coupon! C 1 Sends Block 1 C3C3 C2C2 C1C1 C6C6 C5C5 C4C4 B1 C 3 Sends Block 2 B2 C 2 Sends Block 2 B1B2 C 5 Sends Block 2 B2 B1 is STILL missing!!

5 5 Network Coding  Let a file has k blocks: [B 1 B 2 … B k ]  Encoded block E i is generated by E i = a i,1 *B 1 + a i,2 *B 2 + … + a i,k *B k a i,x : randomly chosen over the finite field  Any “k” linearly independent coded blocks can recover [B 1 B 2 … B k ] by matrix inversion  Network coding maximizes throughput and minimizes delay a 1,1 =1 a 1,2 =0 Coded Block 10 E1E1 Coded Block 11 E2E2 Matrix Inversion B110 B201 B1 B2 a 2,1 =1 a 2,2 =1 Network coding over the finite field GF(2)={0,1}

6 6 Network Coding Helps Coupon Collection C 1 Sends Block 1 C3C3 C2C2 C1C1 C6C6 C5C5 C4C4 B1 C 3 Sends Block 2 B2 C 2 Sends a Coded Block: B1+B2 B1B2 B1+B2 B1 C 5 Sends a Coded Block: B1+B2 B1+B2 B2B1 C 4 a nd C 6 successfully recovered both blocks

7 7 Outline  Previous Work: CarTorrent  Basic Idea  CodeTorrent  Simulation  Conclusion

8 8 Previous Work: Cooperative Downloading with CarTorrent Internet Downloading Blocks from AP Exchange Blocks via multi-hop pulling G R Y Y2 Gossiping Availability of Blocks YY Y RRR

9 9 CodeTorrent: Basic Idea Internet Downloading Coded Blocks from AP Outside Range of AP Buffer Re-Encoding: Random Linear Comb. of Encoded Blocks in the Buffer Exchange Re-Encoded Blocks Meeting Other Vehicles with Coded Blocks  Single-hop pulling (instead of CarTorrent multihop) “coded” block B1 File: k blocks B2 B3 BkBk + *a 1 *a 2 *a 3 *a k Random Linear Combination

10 10 Design Rationale  Single-hop better than multihop Multi-hop data pulling does not perform well in VANET (routing O/H is high) Users in multi-hop may not forward packets not useful to them (lack of incentive)!  Network coding Mitigate a rare piece problem Maximize the benefits of overhearing  Exploits mobility Carry-and-forward coded blocks

11 11 CodeTorrent - Beaconing  Periodic broadcasting of peer ID and its code vector  Used for searching helpful nodes: those who have at least one linearly independent code block Red is Helpful!

12 12 CodeTorrent - Single-hop pulling  A peer pulls coded blocks from the helpful peers 1. G pulls a coded block from R 2. G checks helpfulness and repeats GetBlock G sends a GetBlock message to R G R Y R prepares a re-encoded blockR broadcasts the re-encoded block Check helpfulness: If helpful, store it! Random Linear combination

13 13 Simulations - Setup  Qualnet 3.9  IEEE b / 2Mbps  Real-track mobility model (Westwood map) 2.4x2.4 km 2  Distributing 1MB file 4KB/block * 250 blocks 1KB per packet  # of APs: 3 Randomly located on the road sides  Comparing CarTorrent (w/ AODV) with CodeTorrent AODV w/ net-diameter 3 hops CodeTorrent with GF(256) Near UCLA Campus

14 14 Simulation Results  Overall downloading progress 200 nodes 40% popularity Time (seconds) Fraction of the # pieces/rank of all the interested nodes

15 15 Simulation Results  Avg. number of completion distribution 200 nodes 40% popularity Time (seconds)

16 16 Simulation Results  Multi-hop pulling in CarTorrent As content spreads, CarT shows locality 200 nodes 40% popularity CarTorrent Time (seconds) Avg. hop count exceeding 1 hop

17 17 Simulation Results  Impact of mobility Speed helps disseminate from AP’s and C2C Speed hurts multihop routing (CarT) Car density+multihop promotes congestion (CarT) 40% popularity Avg. Download Time (s)

18 18 Conclusion  Multihop-based CarTorrent: Not scalable due to routing overhead Cooperation may be a problem Coupon problem  CodeTorrent: Scales to mobility; favors cooperation; eliminates a coupon problem  Future work Modeling the impact of mobility CodeTorrent testbed

19 19 Simulation Results  Novelty of coded blocks As speed increases, novelty improves


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