A popularitybased query scheme in P2P networks us

Authors: Leila Sharifi Siavash Khorsandi

Publish Date: 2012/05/01

Volume: 6, Issue: 1, Pages: 75-85

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Abstract

As P2P networks such as many forms of social networking have been rapidly growing numerous efforts have been made to improve the efficiency of the search operation especially in terms of response time and hit ratio To this end popularitybased schemes have recently attracted attention aimed at increasing search efficiency using content popularity ranking however these methods suffer from high cost and overhead or inappropriate level of accuracy in specifying the popularity In this paper we propose an adaptive sampling scheme to make a tradeoff between cost and accuracy This scheme relies on exchanging File Index Table FIT between peers in a local neighborhood using a Gossip Exchange Method GEM The proposed Hybrid Adaptive Search According to Gossip Exchange Method HASAGEM is based on smart unstructured peer to peer overlays We apply a hybrid overlay that efficiently combines topologyaware and interestbased links instead of random or DHT invoked connections An analytical model as well as a simulation framework is developed to illustrate the performance of this scheme The effectiveness of the proposed scheme is demonstrated under various conditions Simulation results reveal that HASAGEM performs well for largescale networks exploiting local content popularity when each local area contains enough number of peers

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