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Gia : Making Gnutella-like P2P Systems Scalable

Gia : Making Gnutella-like P2P Systems Scalable. HY558 Giorgos Saloustros (gesalous@csd.uoc.gr). Roadmap. Introduction P2P systems Distributed Hash Tables (DHT) Gia Design And Implementation Evaluation Questions. Roadmap. Introduction P2P systems Distributed Hash Tables (DHT)

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Gia : Making Gnutella-like P2P Systems Scalable

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  1. Gia: Making Gnutella-like P2P Systems Scalable HY558 GiorgosSaloustros (gesalous@csd.uoc.gr)

  2. Roadmap • Introduction • P2P systems • Distributed Hash Tables (DHT) • Gia Design And Implementation • Evaluation • Questions

  3. Roadmap • Introduction • P2P systems • Distributed Hash Tables (DHT) • Gia Design And Implementation • Evaluation • Questions

  4. P2P Systems • Distributed Systems that have no central servers • Peers forms an overlay network • All peers have equivalent functionalities • Advantages: Scalability, Resource utilization, Reducing administrative costs • Look Up operation is the main problem all P2P networks need to address

  5. Early P2P Systems • Napster • Centralized file index • P2P file transfer • Gnutella (GNU + Nutella) • Unstructured overlay network, topology and placement of files unconstained • Uses simple flooding for file search among peers • KaZaA • Supernodes and Ordinary nodes • Flooding between Supernodes

  6. Distributed Hash Tables (DHT) • Hash Tables Distributed over multiple nodes • LookUp operation requires O(logn) steps • Examples: Chord • Why not use DHT? • Sensitive in High Churn Rate • Need for Keyword Searches • Look for popular objects

  7. Roadmap • Introduction • P2P systems • Distributed Hash Tables (DHT) • Gia Design And Implementation • Evaluation • Questions

  8. Gia • Goals • Scalability • Higher Aggregate Query Rates(!) • Gia design principles • Topology Adaptation: Nodes are Closer to High Capacity Nodes • Flow Control • One-hop replication of content info • Biased Random Walks

  9. Topology Adaptation • Bootstrapping via host cache or equivalent schemes • Construction of an overlay network with low capability nodes close to high capability nodes • Use of satisfaction metric • Number of Peers [min_nbrs, max_nbrs]

  10. The Algorithm

  11. Satisfaction Calculation Algorithm

  12. Satisfaction Calculation Algorithm • Each Node recalculates S in a time gap • T maximum interval between iterations • K aggressiveness of the adaptation

  13. Flow Control • Active flow control assigns tokens to neighbours • X forwards a query to Y only if X has received a token from Y • Elimination of query packets dropping since gia uses random walks • Token allocation rate varies on query-processing capability and buffer queue of every peer • Start-time Fair Queueing is used with weight as the neighbours’ advertized capacity

  14. One-hop replication • Content information is exchanged during connection and updated incrementally • High capacity peers act as proxy for low capacity peers

  15. Search Protocol • Random walk to highest capability peer with flow token received • Uses GUID to send queries to different paths • TTL and max_responses bounds propagation • Advantage: Reduce flooding / congestion • Disadvantage: Sensitive to peer failures • Solution: keep-alive messages, with app-level retries

  16. Roadmap • Introduction • P2P systems • Distributed Hash Tables (DHT) • Gia Design And Implementation • Evaluation • Questions

  17. Evaluation • Gia is compared with • FLOOD – Gnutella model • RWRT – random walks over random topologies • SUPER – KaZaA model, flooding only between super nodes • Query rate is equal for all peers, bounded only from their capacity

  18. Evaluation • Gia: Random graph with topology adaptation. TTL=1024 • min_nbrs = 3, max_nbrs = 128 • Min_alloc=4 • max_nbrs = min(max_nbrs, Capacity/min_alloc) • RWRT: Random graph with uniform degree distributions. TTL=1024. Average degree = 8. • FLOOD: Random graph with uniform degree distributions. TTL=10. Average degree = 8. • SUPER: Random graph for supernodes. Ordinary nodes connect randomly to one super node (TTL=10).

  19. Gia Performance metrics

  20. CP and CP-HC • Collapse Point (CP) the per node query rate at the knee where the query rate drops below 90%. CP is the metric for the total system capacity • Hop-count before collapse (CP-HC) average hop count before collapse

  21. Performance Comparison • Max Responses = 1

  22. Multiple Search Responses

  23. Factor Analysis

  24. Impact of heterogenity

  25. Robustness CP CP-HC

  26. Questions?

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