Enhancing and Analyzing Search performance in Unstructured Peer to Peer Networks Using Enhanced Guided search protocol (EGSP)

TL;DR

This paper introduces the Enhanced Guided Search Protocol (EGSP) to improve search efficiency in unstructured P2P networks by leveraging user interest patterns within a probabilistic framework, supported by theoretical and experimental validation.

Contribution

It proposes a novel search protocol and routing update mechanism that self-organizes unstructured P2P networks into small worlds, enhancing search performance based on user interest modeling.

Findings

Improved search success rate in large unstructured P2P networks.

Reduced search time through network self-organization.

Validated effectiveness via theoretical and experimental analysis.

Abstract

Peer-to-peer (P2P) networks establish loosely coupled application-level overlays on top of the Internet to facilitate efficient sharing of resources. It can be roughly classified as either structured or unstructured networks. Without stringent constraints over the network topology, unstructured P2P networks can be constructed very efficiently and are therefore considered suitable to the Internet environment. However, the random search strategies adopted by these networks usually perform poorly with a large network size. To enhance the search performance in unstructured P2P networks through exploiting users' common interest patterns captured within a probability-theoretic framework termed the user interest model (UIM). A search protocol and a routing table updating protocol are further proposed in order to expedite the search process through self organizing the P2P network into a small world. Both theoretical and experimental analyses are conducted and demonstrated the effectiveness and efficiency of the approach.