Peer Clustering and Firework Query Model
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eer Clustering and Firework Query Mode Cheuk-Hang Ng and Ka-Cheung Sia Cheuk-Hang Ng and Ka-Cheung Sia Department of Computer Science & Engineering The Chinese University of Hong Kong {chng,kcsia}@cse.cuhk.edu.hk 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. Multimedia Information Processing Lab http://www.cse.cuhk.edu.hk/~miplab Contributions • Key Problems In brute force search algorithm, broadcasting the query across the network causes: Peer Clustering 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 Experiment Investigates the effect of query efficiency subject to: Figure 2: Firework Query Figure 1: Peer Clustering • Heavy network traffic • Waste resources in handling irrelevant queries • Increasing the network size • Increasing the Time To Live (TTL) of query message Proposed the Peer Clustering and Firework Query Model improve query efficiency: 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 • • • Firework Query Model • • • 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 Selected References [1] [2] [3] • Reducing the network traffic • Increasing the searching performance attracti ve links Number of query messages against number of peers Number of query messages against TTL of query message Query efficiency against number of peers Recall against TTL of query message
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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. - PowerPoint PPT Presentation
Transcript of Peer Clustering and Firework Query Model
Peer Clustering and Firework Query ModelPeer Clustering and Firework Query ModelCheuk-Hang Ng and Ka-Cheung SiaCheuk-Hang Ng and Ka-Cheung Sia
Department of Computer Science & EngineeringThe Chinese University of Hong Kong
{chng,kcsia}@cse.cuhk.edu.hk
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.
Multimedia Information Processing Labhttp://www.cse.cuhk.edu.hk/~miplab
Contributions•
Key ProblemsIn brute force search algorithm, broadcasting the query across the network causes:
Peer Clustering
Use our clustered network to route the query intelligently rather than by brute force searchQuery 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
ExperimentInvestigates the effect of query efficiency subject to:
Figure 2: Firework Query
Figure 1: Peer Clustering
• Heavy network traffic• Waste resources in handling irrelevant queries
• Increasing the network size • Increasing the Time To Live (TTL) of query message
Proposed the Peer Clustering and Firework Query Model improve query efficiency:
Cluster peers with similar characteristic togetherOn 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
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Firework Query Model•
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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.
Selected References[1]
[2]
[3]
• Reducing the network traffic • Increasing the searching performance
attractive links
Number of query messages against number of peers Number of query messages against TTL of query message
Query efficiency against number of peers Recall against TTL of query message
