Semantic peer, here are the neighbors you want!

Peer Data Management Systems (PDMSs) have been introduced as a solution to the problem of large-scale sharing of semantically rich data. A PDMS consists of semantic peers connected through semantic mappings. Querying a PDMS may lead to very poor results, because of the semantic degradation due to the approximations given by the traversal of the semantic mappings, thus leading to the problem of how to boost a network of mappings in a PDMS. In this paper we propose a strategy for the incremental maintenance of a flexible network organization that clusters together peers which are semantically related in Semantic Overlay Networks (SONs), while maintaining a high degree of node autonomy. Semantic features, a summarized representation of clusters, are stored in a “light” structure which effectively assists a newly entering peer when choosing its semantically closest overlay networks. Then, each peer is sup- ported in the selection of its own neighbors within each over- lay network according to two policies: Range-based selection and k-NN selection. For both policies, we introduce specific algorithms which exploit a distributed indexing mechanism for efficient network navigation. The proposed approach has been implemented in a prototype where its effectiveness and efficiency have been extensively tested.