Peer Clustering and Firework Query Model

1. Peer Clustering and Firework Query Model Selected References A. Lee, M. Lyu and Irwin King. Agent-based multimedia data sharing platform. In Proceedings of the International Symposium of Information Systems and Engineering, volume 1, Las Vegas, Nevada, USA, June 2001. The gnutella homepage. In http://www.gnutella.com. I. Stoica, R. Morris, D. Karger, M.F. Kaashoek and H. Balakrishman. Chord: A scalable peer-to-peer lookup service for internet application. In Proceedings of ACM SIGCOMM, pages 149-160, August 2001. [1] [2] [3] Cheuk-Hang Ng and Ka-Cheung Sia Department of Computer Science & Engineering The Chinese University of Hong Kong {chng,kcsia}@cse.cuhk.edu.hk Multimedia Information Processing Labhttp://www.cse.cuhk.edu.hk/~miplab This poster presents two new strategies for information retrieval over the Peer-to-Peer (P2P) network, called Peer Clustering and Firework Query Model. The Peer Clustering technique organizes peers sharing similar properties together, thus, data inside the P2P network are arranged in a fashion like Yellow Pages. In Firework Query Model, the query first walks around the network from peer to peer randomly, once it reaches the target cluster, the query message is broadcasted to all peers inside the cluster much like an exploding firework. Key Problems In brute force search algorithm, broadcasting the query across the network causes: Peer Clustering Cluster peers with similar characteristic together On top of the original network, we form deliberate attractive links to group peers together (Figure 1) Organize data inside the network in a Yellow Page fashion which makes query more systematic • Heavy network traffic • Waste resources in handling irrelevant queries • Contributions Proposed the Peer Clustering and Firework Query Modelimprove query efficiency: Firework Query Model Use our clustered network to route the query intelligently rather than by brute force search Query first randomly walks around the network, once it reaches the target cluster, the query is broadcasted as a firework explosion (Figure 2) Avoid unnecessary traffic while fully utilize each query message • Reducing the network traffic • Increasing the searching performance Experiment Investigates the effect of query efficiency subject to: • Increasing the network size • Increasing the Time To Live (TTL) of query message Number of query messages against number of peers Number of query messages against TTL of query message attractive links Query efficiency against number of peers Recall against TTL of query message Figure 1: Peer Clustering Figure 2: Firework Query