A Query-Strategy-Focused Taxonomy and a Customizable Benchmarking Framework for Peer-to-Peer Information Retrieval Techniques

P2P IR techniques are gaining momentum in both academic and industrial research communities, mainly due to the fact that they are extensively used-in-practice in a wide set of advanced applications ranging from e-business to e-government and e-procurement systems. P2P IR research is devoted to design innovative search strategies over P2P networks, whit the goal of making these strategies as more efficient and sophisticated as possible. In this respect, benchmarking P2P IR techniques is a leading aspect, and, at the same time, a non-trivial engagement as modeling the strongly decentralized nature and the rapidly-evolving dynamics of real-life P2P systems is still an open and un-completely solved research challenge. Starting from the proposal of a taxonomy of P2P IR techniques, which emphasizes the query strategy used to retrieve information and knowledge from peers, this paper focuses on a customizable benchmarking framework that allows us to study, analyze, and benchmark P2P IR techniques according to several useful metrics, and under the ranging of a number of input parameters. Finally, a comparative analysis of some state-of-the-art P2P IR techniques developed on top of the proposed frame-work is presented and discussed in detail. This analysis further confirms the effectiveness and the reliability of our benchmarking framework for P2P IR techniques.