An Enhanced Search Technique for Managing Partial Coverage and Free Riding in P2P Networks

TL;DR

This paper introduces a Q-learning based routing scheme for unstructured P2P networks that effectively manages free riders, improves hit ratio, reduces traffic, and addresses partial coverage issues.

Contribution

It proposes a novel Q-learning based approach for query routing that selectively uses high-performing peers to enhance network efficiency and robustness.

Findings

Effectively manages free riders in P2P networks

Increases query hit ratio significantly

Reduces overall network traffic

Abstract

This paper presents a Q-learning based scheme for managing the partial coverage problem and the ill-effects of free riding in unstructured P2P networks. Based on various parameter values collected during query routing, reward for the actions are computed and these rewards are used for updating the corresponding Q-values of peers. Thus, the routing is done through only nodes which have shown high performance in the past. Simulation experiments are conducted in several times and the results are plotted. Results show that the proposed scheme effectively manages free riders, generates high hit ratio, reduces network traffic and manages partial coverage problem.