Routing Indices For Peer-to-Peer Systems

1. Routing Indices For Peer-to-Peer Systems Svetlana Strunjas University of Cincinnati May,2002

2. Outline • Motivation and background • P2P systems • Routing Indices • Experimental results • Conclusions

3. Motivation • Create efficient and feasible distributed – index search mechanism for P2P systems

4. Background • Napster – centralized indices (vulnerable to attack and difficult to scale) • Gnutella – queries flood significant part of the network(simple but very costly approach)

5. Background(cont’d 1) • Freenet – each node builds an index with the location of recently requested documents (queries are restricted to the specific documents and it takes time for node to build an effective index)

6. Background(cont’d 2) • Oceanstore – distributed – index approach similar to Routing Indices(special case of Compound RIs) • Key difference is in static network and queries on document identifier (Oceanstore) versus dynamic network and queries on content of document(Routing Indices)

7. Background(cont’d 3) • Selecting a neighbor for forwarding query using Routing Indices is generalization of the Bellman-Ford algorithm • Bellman – Ford algorithm -transmits packet between two nodes through the shortest route -destination of packet is pre-defined(IP routing) • Routing Indices -transmit packet from node to node in order to find best answer to the query -destination of packet is not pre-defined , but instead depends on query contained in packet

8. P2P Systems(Introduction) • Formed by a large number of nodes that can join or leave the system at any time and have equal capabilities • Each node has local documents database which can be accesed through local index • The local index receives content queries and returns pointer to the document with requested content

9. Query Processing in Distributed P2P Systems • Users submit queries to any node along with the stop condition • Node receives query , evaluates the query against it’s own database ,returns pointer to any results , and , if the stop condition is not reached , forwards the query to neighbor(s)(parallel or sequentially)

10. Routing IndicesIntroduction • RI allows a node to select “best“ neighbors to send a query to • It is data structure(and associated algorithm) which ,for given query , returns a list of neighbors , rank according to their goodness for query • Goodness reflects the number of documents in “nearby” nodes

11. Routing Indices Types • Compound Routing Indices(CRI) • Hop-count Routing Indices(HRI) • Exponential Routing Indices(ERI)

12. Compound Routing Indices(example)

13. CRI(cont’d1) • Documents are on zero or more topics,and queries request documents on particular topic • Each node has a local index for quickly finding local documents • CRI contain the number of documents along each path and the number of documents of each topic of interest

14. CRI(“goodness” estimators) • Measure of “goodness” of the neighbor , for given query , is number of documents that can be found in that path • Estimated number of results along each path is given by formula:

15. CRI(drawbacks) • CRI do not take into account the difference in cost due to the number of hops necessary to reach the document • Are not applicable if we have cycles in network

16. Using RI RIs with four topics of interests : database,network,theory and languages

17. Storage space required • It can be adjusted by increasing or decreasing the level of summarization of index • For centralized systems it is C*(T+1)*N bytes • For distributed systems it is C*(T+1)*B*N C – number of categories T – counter size in bytes B – branching factor N – number of nodes

18. Creating (maintaining)RIs

19. 150 75 0 75 125 1500 110 80 70 165 Disconnection from Network

20. Algorithm for Creating/Updating RIs • There are two phases : 1.Newly connected node sends a summary of its local index to its new neighbors (creation phase) 2.The node waits for update messages or for changes on its local index ; after updating its RI , the node sends a new aggregate RIs to all its neighbors

21. Algorithm for Answering Queries • It runs every time query is received • Query is given together with stop condition • There are three phases: 1.Node attempts to answer the query using its local db 2.If not enough results are obtained to reach stop condition , the algorithm ranks all the neighbors using estimating function 3.Node sends the query to each neighbors sequentially,checking if the stop condition was reached whenever each query returns

22. Hop-count RI • Store aggregated RI for each “hop” up to a maximum number of hops(horizon of the RI)

23. Hop-count RI(cont’d1) • Goodness of neighbor is defined as ratio between the number of documents available through that neighbor and the number of messages required to get those documents • Simple model that allows us to compute this ratio is regular-tree model

24. Hop-count RI(cont’d2) • Model assumes that all nodes are connected to exactly F+1 nodes , except ones at the leaves which are connected to only one • Goodness of the neighbor is given by formula: goodness() – estimating function for CRI Ni[j] –RI entry for j hops through i-th neighbor F-fanout H-horizon

25. Hop-count RI(drawbacks) • HRI performances can be negatively affected by the lack of information beyond the horizon • Higher storage and transmission cost than CRI

26. Exponentially Aggregated RI • Stores the result of applying the regular-tree cost formula to hop-count RI

27. Exponentially Aggregated RI(cont’d) • Each entry of the ERI for node N contains a value computed as: • th – height of the assumed regular tree • goodness() – estimating function for CRIs • N[j] – summary of the local index of neighbor j of N • T – topic of inerest for entry • With ERIs we can keep information for all nodes accessible from each neighbor in the RI,while HRI’s do not have any information beyond horizon

28. Cycles in P2P Network There are three approaches for dealing with cycles: • No-op solution • Cycle avoidance solution • Cycle detection and recovery

29. No-op solution • Works only with the HRI and ERI • If there are cycles CRI algorithm can be trapped in an infinite loop

30. G2=23.58 NO-op solution (cont’d1) 10 15 G1=21.67 20

31. NO-op solution (cont’d2) • In HRI cycles longer than horizon will not affect the RI • If we use regular-tree cost model we can limited effect of short cycles • In HRI and ERI difference between two values of goodness introduced by cycle is very small(algorithm will not propagate updates which are not much different than old value)

32. Cycle avoidance solution • Do not allow nodes to create an update connection to other node if such connection creates the cycle • Drawback : Absence of global information causes suboptimal update network

33. Cycle detection and recovery • Detects cycles sometime after they are formed and takes recovery actions to eliminate the effect of the cycles • Cycles are detected using unique message identifier • Recovery procedure can decrease accuracy of the RI

34. Experimental Results(Introduction) • Results are obtained using different models for elements of search mechanism • Steps of experiment: 1.Setting P2P system as network of nodes T, where each node contains set of documents 2.Users send requests consisting of query Q and stopCondition to a node of P2P system 3. search mechanism answers requests by obtaining a set of documents of size stopCondition that matches Q 4.search mechanism allows for update such as addition of nodes and new documents

35. Experimental Results(Techniques and measure of cost) • Search techniques : CRI , HRI , ERI, No-RI(for comparison purposes) • Measure of cost:numbers of messages generated

36. Experimental Results(Network topologies) • Topology of network defines number of nodes and how they are connected • In this model , three kinds of topologies are considered: 1.Tree 2.Tree with added cycles 3.Power-law graph

37. Experimental Results(Distribution of documents) • Distributions for modeling the location of document results : 1.Uniform distribution( all nodes have the same probability of having each document result) 2.80/20 biased distribution ( assigns uniformly 80% of the document results to the 20% of nodes , and the remaining 20% of the documents to the remaining 80% of nodes)

38. Experimental Results(Simulation parameters)

39. Experimental Results(Comparison of CRI,HRI and ERI)

40. Experimental Results(Number of results)

41. Experimental Results(Effects of overcounts)

42. Experimental Results(Effects of cycles)

43. Experimental Results(Network topology)

44. Experimental Results(Updates and network topology)

45. Experimental Results(Updates and cycle policy)

46. Experimental Results(Updates per minute)

47. Conclusions • ERI and HRI offer significant improvements versus not using an RI,while keeping update costs low • Routing indices (in particular ERI and HRI can help improve the search performance of current and future P2P systems

48. References: [1] A.Crespo , H. Garcia-Molina.Routing Indices For Peer-to-Peer Systems(2001).The 22nd International Conference on Distributed Computing Systems ,Vienna , Austria. [2] J.F.Kurose , K.W.Ross.(1999).”Routing Principles”.Computer Networking – A Top Down Approach Featuring Internet, 2nd ed. , Addison Wesley,4.