CISS: An Efficient Object Clustering Framework for DHT-Based Peer-to-Peer Applications

Distributed Hash Tables (DHTs) have been widely adopted in many Internet-scale P2P systems. Emerging P2P applications such as massively multi player online games (MMOGs) and P2P catalog systems frequently update data or issue multi-dimensional range queries, but existing DHT-based P2P systems can not support these applications efficiently due to object declustering. Object declustering can result in significant inefficiencies in data update and multi-dimensional range query routing. In this paper, we propose CISS, a framework that supports efficient object clustering for DHT-based P2P applications. While utilizing DHT as a basic lookup layer, CISS uses a Locality Preserving Function (LPF) instead of a hash function. Thus, CISS achieves a high level of clustering without requiring any changes to existing DHT implementations. Technically, we study LPF encoding function, efficient routing protocols for data updates and multi-dimensional range queries, and cluster-preserving load balancing. We demonstrate the performance benefits of CISS through simulation.

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