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Can Heterogeneity Make Gnutella Scalable?

Can Heterogeneity Make Gnutella Scalable?. Gisik Kwon Dept. of Computer Science and Engineering Arizona State University. Motivation. Scalability of Gnutella TTL-basd flooding Pros: easily accommodate highly transient node population Cons No guarantee to locate existing file

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Can Heterogeneity Make Gnutella Scalable?

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  1. Can Heterogeneity Make Gnutella Scalable? Gisik Kwon Dept. of Computer Science and Engineering Arizona State University

  2. Motivation • Scalability of Gnutella • TTL-basd flooding • Pros: easily accommodate highly transient node population • Cons • No guarantee to locate existing file • No scalablility • Improving scalability • Higher capacity nodes carry the heavier burdens • Random walks searching

  3. Design • Main features • Flow control: Restrict flow of queries into each nodes • Topology adaptation: query flow toward a sufficient capacity node • Terms • Ci: maximum # messages node I is able to process over a given time interval T • In[j,i]: # incoming messages from node j to I in the last time interval T • Out[I,j]: # outgoing messages from node i to j in the last time interval T • outMax[I,j]: maximum # messages node I can send to node j per time interval T • Out[I,j] <= outMax[I,j] <= out[I,j] + (Cj – in[*,j])

  4. Pseudo code

  5. Evaluation • Setup • =10, =1.25, T=100 seconds • Object popularity: Zipf-like distribution( = 1.2) • Query rate: poisson process(1.2 queries/min) • Node heterogeneity • Ci: Zipf-like distribution( = 2.0) • Bandwidth distribution: from measurement • Dial-up modem(a fair fraction), cable or DSL(majority), high speed(small portion) • Uniform random graph topology • For Zipf-like capacity distribution • 10000 nodes, avg. degree 9.9 • For Gnutella-like capacity distribution • 5000 nodes, avg. degree 7.5

  6. Average query resolution time

  7. Query resolution

  8. Degree distribution

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