A recall-based cluster formation game in peer-to-peer systems

Abstract

In many large-scale content sharing applications, participants or peers are grouped together forming clusters based on their content or interests. In this paper, we deal with the maintenance of such clusters in the presence of updates. We model the evolution of the system as a strategic game, where peers determine their cluster membership based on a utility function of the query recall. Peers are guided either by selfish or altruistic motives: selfish peers aim at improving the recall of their own queries, whereas altruistic peers aim at improving the recall of the queries of other peers. We study the evolution of such clusters both theoretically and experimentally under a variety of conditions. We show that, in general, local decisions made independently by each peer enable the system to adapt to changes and maintain the overall recall of the query workload.

PeerSum: a summary service for P2P applications

“…(Oser et al (2003)). According to this classi‐fication, there are hybrid techniques such as caching data indexes (Wang et al , 2006), or clustering a P2P network based on index similarity (Koloniari et al , 2003).…”