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Sustaining Cooperation in Multi-Hop Wireless Networks

Sustaining Cooperation in Multi-Hop Wireless Networks. Ratul Mahajan, Maya Rodrig, David Wetherall and John Zahorjan University of Washington Presented by: Prasad (Slides in courtesy of: Bin Ni, University of South Carolina). Key words. Wireless network

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Sustaining Cooperation in Multi-Hop Wireless Networks

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  1. Sustaining Cooperation in Multi-Hop Wireless Networks Ratul Mahajan, Maya Rodrig, David Wetherall and John Zahorjan University of Washington Presented by: Prasad (Slides in courtesy of: Bin Ni, University of South Carolina)

  2. Key words • Wireless network - characteristic of broadcasting • Multi-Hop - a packet may be forwarded by multi nodes • Free-rider and Cooperation - less contribution to the group - consume more than their fair share of a resource

  3. Topics • Problem Definition • The power of Anonymity • The Catch Protocol • Experimental Evaluation • Simulation and Analysis

  4. Problem Definition • B can avoid these forwarding loads in two distinct ways: - forwarding level : drop packets for forwarding from A - routing level : refuse to send routing messages that acknowledge connectivity with A

  5. Assumptions • Most nodes are cooperative in that they run the protocol defined; • Omni-directional radio transmitters and antennas; • Nodes have unforgeable ID.

  6. Power of Anonymity • The goal is to use cooperative nodes to monitor for the presence of free-riders and to isolate them. • Two problems - distinguish them - signal all of the free-rider’s neighbor

  7. Anonymous Challenges and Watchdogs • A watchdog is used; • Anonymous challenge message (ACM) sub-protocol is defined; • Gateway regularly but unpredictably sends an anonymous challenge to the testee to rebroadcast.

  8. Anonymous Neighbor Verification • Once free-rider is detected, other testers must also be informed; • Challenge: the only path must be via the testee; • Anonymous neighbor verification (ANV) sub-protocol is defined;

  9. Anonymous Neighbor Verification • ANV open - all the testers become aware of each other via the testee; - each tester sends a cryptographic hash of a randomly generated token; - testee rebroadcasts, other testers take note; • ANV close - each tester releases its token to the testee if it behaved well; - the testee broadcasts the token; - testers compare the received token;

  10. Catch protocol • Epoch-Start - testee broadcasts packet that includes its ID and epoch ID; - nodes that receives the packets participate as testers for this epoch; • Packet Forwarding and Accounting - testers run a watchdog to count the number that are correctly relayed; - testers run the ACM protocol to estimate true connectivity; • Anonymous Neighbor Verification Open - tester sends an anonymous packet containing a nonce and a hashed token to the testee for rebroadcast

  11. Catch protocol • Tester Information Exchange - tester compares the fraction of data packets and challenges; - one-bit sign:0 for challenges and 1 for data packets; - send the sign bit and ID to testee for rebroadcasting ; • Epoch Evaluation and ANV close - each testers determine whether the testee behaviors correctly - this is done with a pair of statistical test - both tests pass, the tester releases its token; • Isolation Decision

  12. Protocol flow: packets exchange between a tester and a cooperative (left side) or free-riding (right side) testee.

  13. Evaluation • 15 PCs equipped with 802.11b • Operating in the ad-hoc mode • Diameter is between 3 and 5 hops • Length of one epoch is set to one minute • There are 15 anonymous ACM messages per epoch

  14. Evaluation • Three nodes: the second one acts as free-rider • The number of epochs required to detect free-riders in the testbed versus the fraction of packets a free-rider dropped. • Each point is the average of 10 experiments.

  15. Evaluation • Three nodes are free-riders that drop all the packets ; • Nodes select only cooperative nodes as file servers; • It shows that the cooperative nodes successfully shut up the free-riders;

  16. Evaluation • We ran two five hour experiments in which all nodes were cooperative. • Each node repeatedly downloaded les from randomly chosen servers. • We observed no false positives in the first experiment and a single false positive in the second.

  17. Evaluation • cheater that uses signal strength to differentiate among its neighbors. • For example, when 20% (3) of the nodes cheat, that probability is lowered from about 60% to about 10% when using the highest quality links.

  18. Simulation and Analysis • the impact of high wireless loss rates on Catch is quite small. • Catch seems to be robust, working well in both high and low density networks.

  19. Future work • Collusion of the free riders • Taking specific steps in Catch to discourage signal strength based cheats

  20. Thanks! Any question?

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