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Exploring Tradeoffs in Failure Detection in P2P Networks

Exploring Tradeoffs in Failure Detection in P2P Networks. Shelley Zhuang, Ion Stoica, Randy Katz Sahara Retreat January, 2003. Problem Statement. One of the key challenges to achieve robustness in overlay networks: quickly detect a node failure

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Exploring Tradeoffs in Failure Detection in P2P Networks

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  1. Exploring Tradeoffs in Failure Detection in P2P Networks Shelley Zhuang, Ion Stoica, Randy Katz Sahara Retreat January, 2003

  2. Problem Statement • One of the key challenges to achieve robustness in overlay networks: quickly detect a node failure • Canonical solution: each node periodically pings its neighbors • Study the fundamental limitations and tradeoffs between detection time, control overhead, and probability of false positives • Determine the optimal control resource allocation strategy for a given network topology, failure rate, and load distribution

  3. Network Model • P2P system with n nodes • Each node A knows d other nodes • Average path length = l

  4. Failure Model • Failure rate of each node is λf • Node up-time ~ i.i.d. T = exponential(λf) • Failstop failures • If a neighbor is lost, a node can use another neighbor to route the packet w/o affecting the path length

  5. Packet Loss Probability • δ = average time it takes a node to detect that a neighbor has failed • Probability that a node forwards a packet to a neighbor that has failed is 1- e-λf δδλf P(T-t  δ | Tt) = P(T<=δ) • Probability that the packet is lost is pl lδλf pdf T δ

  6. Aliveness Techniques • Baseline • Each node sends a ping message to each of its neighbors every Δ seconds B C A D

  7. Aliveness Techniques • Information Sharing • Piggyback failures of neighbors in acknowledgement messages • Best case: completely connected graph of degree d B C A D

  8. Aliveness Techniques • Information Sharing with Boosting • When a node detects failure of a neighbor, D, it announces to all other nodes that have D as their neighbor • Best case: completely connected graph of degree d B C A D

  9. Case Studies • d-regular network • Chord (PROBE_TO_THRESH) • Constant overhead: T seconds, S probes • Δ = Td/S • Tradeoff between loss probability and size of neighborset, d

  10. d-Regular Network Packet Loss Probability

  11. ChordPacket Loss Probability Sharing w/ boosting (simple)

  12. baseline 3 0. 0000337177 boosting 10 0. 0000121711 ChordProbability of False Positive

  13. Conclusion • Analyzed packet loss probability in a d-regular network • Examined four keep-alive techniques in Chord • By carefully designing keep-alive algorithms, it is possible to significantly reduce packet loss probability w/o additional control overhead • Boosting can achieve both lower packet loss probability and probability of false positive than baseline

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