A dynamically semantic platform for efficient information retrieval in P2P networks

To build a scalable, robust and accurate P2P network, the network must be able to manage efficiently large amounts of information. This paper proposes a semantic-driven model where the network topology is adaptively shaped, based on the peers' semantic knowledge and the association between network size, peer connectivity and frequency of requested concepts. The proposed architecture follows a two-layer approach: the upper layer forms the semantic knowledge of the network through super-peers; the lower layer of peers represents the network resources. The network knowledge is formally represented by a domain-specific ontology using collective intelligence techniques. During the resource discovery process the query is intelligently routed in the semantic layer via ontology-supported decisions; achieving in this way, based on experimental results, higher query success and reduced network traffic. The proposed model has been experimentally evaluated and results show the semantic-driven network outperforms existing P2P networks.