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An Effective and Secure Data Sharing in P2P Network Using Biased Contribution Index Based Rumour Riding Protocol (BCIRR)

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Abstract

Data sharing in the Peer to Peer (P2P) networks became an important function in the trustworthy computing. Secure and load balancing control in file sharing is vital to enhance the overall performance of P2P file sharing system. In literature many methods of load balancing control and security control have been used but it is not able to attain the best results in P2P networks. Hence, in this paper, Biased Contribution Index Based Rumour Riding Protocol (BCIRR) is developed to attain the load balancing control and security enhancement of P2P networks. The proposed method is concentrated to achieve two main objective function such as load balancing control and security enhancement. The proposed protocol is a combination of Biased Contribution Index (BCI) and Enhanced Rumour Riding protocol (ERR). Here, load balancing control of the P2P network is attained with the utilization of the BCI and security enhancement of the P2P network is attained with the utilization of the ERR. The proposed protocol will be implemented in the Matlab platform and the performance of the proposed protocol is analysed with different performance metrics such as Packet loss, Delivery ratio, Average end to end delay and Throughput. To analysis the effectiveness of proposed method, it will be compared with the existing method of Catching Algorithms (CA).

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Authors and Affiliations

  1. Dr. A.P. J Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India

    Dharmendra Kumar

  2. Motilal Nehru National Institute of Technology, Teliarganj, Prayagraj, Uttar Pradesh, India

    Mayank Pandey

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  1. Dharmendra Kumar
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  2. Mayank Pandey
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Correspondence to Dharmendra Kumar.

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Disclosure of potential conflicts of interest: There is no potential of conflict of Interest between the authors regarding the manuscript preparation and submission.

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Kumar, D., Pandey, M. An Effective and Secure Data Sharing in P2P Network Using Biased Contribution Index Based Rumour Riding Protocol (BCIRR). Opt. Mem. Neural Networks 29, 336–353 (2020). https://doi.org/10.3103/S1060992X20040104

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  • DOI: https://doi.org/10.3103/S1060992X20040104

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