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A Scalable Peer-to-Peer Architecture for Distributed Information Monitoring Applications
June 2005 (vol. 54 no. 6)
pp. 767-782
Ling Liu, IEEE Computer Society
We present PeerCQ, a decentralized architecture for Internet scale information monitoring using a network of heterogeneous peer nodes. PeerCQ uses Continual Queries (CQs) as its primitives to express information-monitoring requests. The PeerCQ development has three unique characteristics. First, we develop a systematic and serverless approach to large scale information monitoring, aiming at providing a fully distributed, highly scalable, and self-configurable architecture for scalable and reliable processing of a large number of CQs over a network of loosely coupled, heterogeneous, and possibly unreliable nodes (peers). Second, we introduce an effective service partitioning scheme at the P2P protocol layer to distribute the processing of CQs over a peer-to-peer information monitoring overlay network while maintaining a good balance between system utilization and load balance in the presence of peer joins, departures, and failures. A unique feature of our service partitioning scheme is its ability to incorporate strategies for handling hot spot monitoring requests and peer heterogeneity into the load balancing scheme in PeerCQ. Third, but not least, we develop a dynamic passive replication scheme to enable reliable processing of long-running information monitoring requests in an environment of inherently unreliable peers, including an analytical model to discuss its fault tolerance properties. We report a set of experiments demonstrating the feasibility and the effectiveness of the PeerCQ approach to large-scale peer-to-peer information monitoring.

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Index Terms:
Distributed information monitoring, peer-to-peer networks, continual query systems.
Citation:
Bugra Gedik, Ling Liu, "A Scalable Peer-to-Peer Architecture for Distributed Information Monitoring Applications," IEEE Transactions on Computers, vol. 54, no. 6, pp. 767-782, June 2005, doi:10.1109/TC.2005.87
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