Query Learning-Based Scheme for Pertinent Resource Lookup in Mobile P2P Networks

Abstract

P2P networking has grasped an increasing interest worldwide among both researchers and computer networking professionals. As a witness, several P2P applications mainly used for file sharing over the Internet have been proposed. Considering the great success of mobile devices in recent years, P2P applications have also been deployed over mobile networks such as mobile ad-hoc networks (MANETs). However, the mismatch between the P2P overlay and the MANET underlay topologies makes the resources lookup mechanism in mobile P2P applications very difficult. Therefore, this downside is the main hindrance to the deployment of such applications over MANETs. To overcome the mismatch issue, we propose in this paper RLSM-P2P a cross-layer resource lookup scheme for Mobile P2P applications. The main thrust of RLSM-P2P consists of building an efficient unstructured P2P overlay that closely matches the underlay physical network and swiftly adapts to its volatility and dynamicity by considering different MANET constraints. Furthermore, RLSM-P2P relies on a query learning resource lookup mechanism for locating pertinent resources to user queries. The performed experiments show that RLSM-P2P outperforms its competitors in terms of effectiveness and efficiency.