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Pastry

Pastry. Peter Druschel, Rice University Antony Rowstron, Microsoft Research UK Some slides are borrowed from the original presentation by the authors. Outline. Background Pastry Pastry proximity routing PAST SCRIBE Conclusions. Common issues. Organize, maintain overlay network

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Pastry

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  1. Pastry Peter Druschel, Rice University Antony Rowstron, Microsoft Research UK Some slides are borrowed from the original presentation by the authors

  2. Outline • Background • Pastry • Pastry proximity routing • PAST • SCRIBE • Conclusions

  3. Common issues • Organize, maintain overlay network • Resource allocation/load balancing • Object / resource location • Network proximity routing Pastry provides a generic p2p substrate

  4. Architecture Event notification Network storage ? P2p application layer P2p substrate (self-organizing overlay network) Pastry TCP/IP Internet

  5. Pastry: Object distribution 2128-1 O • Consistent hashing • [Karger et al. ‘97] • 128 bit circular id space • * nodeIds(uniform random) • objIds (uniform random) • Invariant: node with numerically closest nodeId maintains object. (Recall Chord) objId nodeIds

  6. Log 16 N rows Leaf set Routing table for node 65a1fc (b=4)

  7. Pastry: Leaf sets • Each node maintains IP addresses of the nodes with the L/2 numerically closest larger and smaller nodeIds, respectively. • routing efficiency/robustness • fault detection (keep-alive) • application-specific local coordination

  8. Pastry: Routing Properties log16 N steps O(log N) state d471f1 d467c4 Prefix routing d462ba d46a1c d4213f Route(d46a1c) d13da3 65a1fc

  9. Pastry: Routing procedure if destination is within the range of leaf set then forward to numerically closest member else {let l = length of shared prefix} {let d = value of l-th digit in D’s address} if (Rld exists) (Rld = entry at column d row l) then forward to Rld else {rare case} forward to a known node that (a) shares at least as long a prefix, and (b) is numerically closer than this node

  10. Pastry: Performance Integrity of overlay/ message delivery: • guaranteed unless L/2 simultaneous failures of nodes with adjacent nodeIds Number of routing hops: • No failures: < log16N expected, 128/b + 1 max • During failure recovery: • O(N) worst case, loose upper bound, average case much better

  11. Self-organization How are the routing tables and leaf sets initialized and maintained? • Node addition • Node departure (failure)

  12. Pastry: Node addition d471f1 d467c4 d462ba d46a1c d4213f New node: d46a1c The new node X asks node 65a1fc to route a message to it. Nodes in the route share their routing tables with X Route(d46a1c) d13da3 65a1fc

  13. Node departure (failure) Leaf set members exchange heartbeat • Leaf set repair (eager): request the set from farthest live node • Routing table repair (lazy): get table from peers in the same row, then higher rows

  14. Pastry: Average # of hops L=16, 100k random queries

  15. Pastry: Proximity routing Proximity metric = time delay estimated by ping A node can probe distance to any other node Each routing table entry uses a node close to the local node (in the proximity space), among all nodes with the appropriate node Id prefix.

  16. d467c4 d471f1 d467c4 Proximity space d462ba d46a1c d4213f Route(d46a1c) d13da3 d4213f 65a1fc 65a1fc d462ba d13da3 NodeId space Pastry: Routes in proximity space

  17. Pastry: Proximity routing Assumption: scalar proximity metric • e.g. ping delay, # IP hops • a node can probe distance to any other node Proximity invariant Each routing table entry refers to a node close to the local node (in the proximity space), among all nodes with the appropriate nodeId prefix.

  18. Pastry: Distance traveled L=16, 100k random queries, Euclidean proximity space

  19. k=4 fileId Insert fileId PAST: File storage Storage Invariant: File “replicas” are stored on k nodes with nodeIds closest to fileId (k is bounded by the leaf set size)

  20. PAST: File Retrieval C k replicas Lookup file located in log16 N steps (expected) usually locates replica nearest to client C fileId

  21. SCRIBE: Large-scale, decentralized multicast • Infrastructureto support topic-based publish-subscribe applications • Scalable: large numbers of topics, subscribers, wide range of subscribers/topic • Efficient: low delay, low link stress, low node overhead

  22. SCRIBE: Large scale multicast topicId Publish topicId Subscribe topicId

  23. Scribe: Results • Simulation results • Comparison with IP multicast: delay, node stress and link stress • Experimental setup • 100,000 nodes randomly selected out of .5M • Zipf-like subscription distribution, 1500 topics

  24. Summary Self-configuring P2P framework for topic-based publish-subscribe • Scribe achieves reasonable performance when compared to IP multicast • Scales to a large number of subscribers • Scales to a large number of topics • Good distribution of load

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