Mapping data in peer-to-peer systems

TLDR

Peer‑to‑peer data‑sharing systems rely on mapping tables that pair values across peers to locate data. This work investigates the semantic and algorithmic challenges of using mapping tables, arguing for their suitability and the need for reasoning to infer new tables. The authors introduce a language for specifying mapping tables under various semantics, analyze the complexity of reasoning about them, and propose an efficient algorithm that treats mapping tables as constraints. Experiments demonstrate that the proposed algorithm enables efficient management of mapping tables in practice, confirming that constraint‑based reasoning is effective.

Abstract

We consider the problem of mapping data in peer-to-peer data-sharing systems. Such systems often rely on the use of mapping tables listing pairs of corresponding values to search for data residing in different peers. In this paper, we address semantic and algorithmic issues related to the use of mapping tables. We begin by arguing why mapping tables are appropriate for data mapping in a peer-to-peer environment. We discuss alternative semantics for these tables and we present a language that allows the user to specify mapping tables under different semantics. Then, we show that by treating mapping tables as constraints (called mapping constraints) on the exchange of information between peers it is possible to reason about them. We motivate why reasoning capabilities are needed to manage mapping tables and show the importance of inferring new mapping tables from existing ones. We study the complexity of this problem and we propose an efficient algorithm for its solution. Finally, we present an implementation along with experimental results that show that mapping tables may be managed efficiently in practice.