Computing a Deterministic Semantics for P2P Deductive Databases

Abstract

This paper proposes a logic based framework for data integration and query answering for deductive databases in a P2P environment. It is based on a special interpretation of mapping rules that leads to a declarative semantics for P2P systems defined in terms of preferred weak models. Under this semantics, only facts not making the local databases inconsistent can be imported, and the preferred weak models are the consistent scenarios in which peers import, by means of mapping rules, maximal sets of facts not violating (directly or indirectly) integrity constraints. The preferred weak models can be computed by means of a rewriting technique allowing to model a P2P system as a unique logic program whose stable models correspond to its preferred weak models. In the general case a P2P system may admit many preferred weak models and it has been shown that the complexity of their computation is prohibitive. Therefore, the paper looks for a more pragmatic solution assigning to a P2P system a new and more suitable semantics: the Well Founded Model Semantics. It allows to obtain a deterministic model whose computation is polynomial time. This model is a (partial) stable model obtained by evaluating with a three-value semantics the normal version of the rewriting of the P2P system. Finally, a distributed algorithm for the computation of the well founded model is proposed.