1. YAPPERS: A Peer-to-Peer Lookup Service over Arbitrary Topology Qixiang Sun Prasanna Ganesan Hector Garcia-Molina Stanford University

2. Outline Background and Motivation High-level overview of YAPPERS Brief evaluation

3. Problem Where is X?

4. Problem (2) 1. Search 2. Node join/leave 3. Register/remove content A B C

5. Background Gnutella-stylejoin –anywhere in the overlay register –do nothing search –flood the overlay

6. Background (2) Distributed hash table (DHT) join –a unique location in the overlay register –place pointer at a unique node search –route towards the unique node... Chord CAN

7. Background (3) Gnutella-style +Simple +Local control +Robust +Arbitrary topology –Inefficient –Disturbs many nodes DHT +Efficient search –Restricted overlay –Difficulty with dynamism

8. Motivation Best of both worlds –Gnutella’s local interactions –DHT-like efficiency Respect application-defined topology –Social network –Ad hoc wireless network –Physical-network proximity

9. Partition Nodes Given any overlay, first partition nodes into buckets (colors) based on hash of IP

10. Partition Nodes Given any overlay, first partition nodes into buckets (colors) based on hash of IP

11. Partition Nodes (2) Around each node, there is at least one node of each color XY May require backup color assignments

12. Register Content Partition content space into buckets (colors) and register pointer at “nearby” nodes. Z register red content locally register yellow content at a yellow node Nodes around Z form a small hash table!

13. Searching Content Start at a “nearby” colored node, search other nodes of the same color. V U XY Z W

14. Searching Content (2) A smaller overlay for each color and use Gnutella-style flood Fan-out = degree of nodes in the smaller overlay

15. Recap Hybrid approach –Around each node, act like a hash table –Flood the relevant nodes in the entire network What do we gain? –Respect original overlay –Efficient search for popular data –Avoid disturbing nodes unnecessarily

16. Brief Evaluation Using a 24,702 nodes Gnutella snapshot as the underlying overlay We study –Number of nodes contacted per query when searching the entire network –Trade-off in using our hybrid approach when flooding the entire network

17. Nodes Searched per Query Limited by the number of nodes “nearby”

18. Trade-off Fan-out = degree of each colored node when flooding “nearby” nodes of the same color Average Fan-out Vanilla 835 Heuristics 82 Good in searching nearby nodes quickly. Bad in searching the entire network

19. Conclusion Does YAPPERS work? –YES Respects the original overlay Searches efficiently in small area Disturbs fewer nodes than Gnutella Handles node arrival/departure better than DHT –NO Large fan-out (vanilla flooding won’t work)

20. For More Information A short position paper advocating locally- organized P2P systems http://dbpubs.stanford.edu/pub/2002-60 Other P2P work at Stanford http://www-db.stanford.edu/peers

22. Recap node join –anywhere in the overlay register content –at nearby node(s) of the appropriate color search –start at a nearby node of the search color and then flood nodes of the same color.

23. What Do We Gain? Respect original overlay Efficient search for popular data Avoid disturbing nodes unnecessarily Better handling of dynamic node arrival and departure

24. Design Issues How to build a small hash table around each node, i.e., assign colors? How to connect nodes of the same color?

25. Small-scale Hash Table Small = all nodes within h hops (e.g., h=2) –Consistent across overlapping hash tables –Stable when nodes enter/leave A B X C

26. Small-scale Hash Table (2) Fixed number of buckets (colors) Determine bucket (color) based on the hash value of node IP addresses –Multiple nodes of the same color –No nodes of a color

27. Searching the Overlay Find another node of the same color in a “nearby” hash table All nodes within h hops A C B Frontier Node Need to track all nodes within 2h+1 hops

28. Searching the Overlay (2) For a color C and each frontier node v, 1. determine which nodes v might contact to search for color C 2. contact these nodes Theorem: Regardless of starting node, one can search all nodes of all color.

29. Buckets per Node Using 32 buckets (colors) per hash table AVG = 3.7 3.7 32 = 11.5%

30. Overloading a Node A node may have many colors even if it has a large neighborhood. A X