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The Query-Cycle Simulator for Simulating P2P Networks Mario T. Schlosser Tyson E. Condie Sepandar D. Kamvar Stanford University Problem Problem: Accurately Simulate Real-World P2P Networks. Motivation: Testing P2P Algorithms. Goals P2P Simulator Descriptive Simple Easily Extensible Make it available on the web so that people can test and compare their algorithms on a standard platform. Query Cycle Model Query Cycle Model Query Cycle Model Properties to Model Peer Content Network Parameters Peer Behavior Properties to Model Peer Content How Much? What Type? Network Parameters Peer Behavior Data Volume Observations Model Content Type: Observations Content Categories Zipf distribution on file popularity Content Type: Model Modeling Content Categories: Assume n content categories. C={c1,c2,…,cn} A peer i is assigned content categories according to the Zipf distribution: It is then assigned an interest level p(c|i) to each of the assigned content categories by a uniform random distribution. Content Type: Model Modeling Files: Each distinct file f may be uniquely identified by {c,r} A peer is assigned files by: Recap on Content Assignment Recap on Content Assignment Recap on Content Assignment Recap on Content Assignment Recap on Content Assignment Properties to Model Peer Content Network Parameters Topology Bandwidth Peer Behavior Network Parameters Topology: Observation: Power Law Topology Model: probability of connecting to a peer is proportional to the degree of that peer. Bandwidth Simple Bandwidth Model Can be easily extended. Properties to Model Peer Content Network Parameters Peer Behavior Query-Cycle Model At each cycle, peer i may be: active inactive or down Query-Cycle Model At each cycle, peer i may be: active inactive or down Query-Cycle Model At each cycle, peer i may be: active inactive or down Query-Cycle Model At each cycle, peer i may be: active inactive or down Properties to Model Peer Content Network Paramete