A Logic Framework for P2P Deductive Databases

Abstract: This paper presents a logic framework for modeling the interaction among deductive databases in a P2P (Peer to Peer) environment. Each peer joining a P2P system provides or imports data from its neighbors by using a set of mapping rules, i.e. a set of semantic correspondences to a set of peers belonging to the same environment. Two different types of mapping rules are defined: mapping rules allowing to import a maximal set of atoms not leading to inconsistency (called maximal mapping rules) and mapping rules allowing to import a minimal set of atoms needed to restore consistency (called minimal mapping rules). Implicitly, the use of maximal mapping rules states it is preferable to import as long as no inconsistencies arise; whereas the use of minimal mapping rules states that it is preferable not to import unless a inconsistency exists. The paper presents three different declarative semantics of a P2P system: (i) the Max Weak Model Semantics, in which mapping rules are used to import as much knowledge as possible} from a peer's neighborhood without violating local integrity constraints; (ii) the Min Weak Model Semantics, in which the P2P system can be locally inconsistent and the information provided by the neighbors is used to restore consistency, that is to only integrate the missing portion of a correct, but incomplete database; (iii) the Max-Min Weak Model Semantics that unifies the previous two different perspectives captured by the Max Weak Model Semantics and Min Weak Model Semantics. This last semantics allows to characterize each peer in the neighborhood as a resource used either to enrich (integrate) or to fix (repair) the knowledge, so as to define a kind of integrate-repair strategy for each peer. Under consideration in Theory and Practice of Logic Programming (TPLP).