P2P Queries Routing Using Distributed Knowledge

The growing interest in Peer-to-Peer systems (such as Gnutella) has inspired numerous research activities. The problem in a schema-based Peer-to-Peer (P2P) system is how to locate Peers relevant to a given query. Different methods proposed routing strategies of queries taking into account the P2P network at hand. In this paper, we propose an architecture, based on (Super-) Peers, and we focus on query routing. Our approach considers that (Super-) Peers having similar interests are grouped together for an efficient query routing method. In such groups, called Super-Super-Peers (SSP), Super-Peers submit queries that are often processed by members of this group. A SSP is a specific Super-Peer that contains knowledge about: 1. its Super-Peers and 2. The other SSP. Knowledge is extracted by using data mining techniques (e.g. decision tree algorithms) starting from queries of Peers that transit on the network. The advantage of this distributed knowledge is that, it avoids making semantic mapping, between heterogeneous data sources owned by (Super-)Peers, each time the system decides to route query to other (Super-)Peers. The set of SSP improves the robustness in queries routing mechanism and scalability in P2P Network. Compared with a baseline approach, our proposed architecture shows that data mining technique increase performance with respect to response time and precision.