Title: Retaliation-based secured model for enhanced weighted clustering algorithm in mobile ad-hoc network

Authors: Naghma Khatoon; Amritanjali

Addresses: Department of Computer Science and Engineering, Birla Institute of Technology, Mesra 835215, Ranchi, India ' Department of Computer Science and Engineering, Birla Institute of Technology, Mesra 835215, Ranchi, India

Abstract: Mobile Ad-hoc Networks (MANETs) are wireless networks without any fixed infrastructure, consisting of autonomous mobile devices that are interconnected via wireless media. In the recent years MANETs have become one of the most prevalent areas of research because of their inevitable characteristics. However, resource limitations, energy efficiency, scalability and security are the major challenging concerns in MANETs. In this paper, we propose a novel methodology for a secure and fair weighted clustering algorithm using a combination of four parameters: stability factor, degree deviation, sum of distances to a node's neighbours and energy depletion. Our proposed algorithm revolves around three important advantages for clustering. The first is to eliminate the non-eligible nodes to become a cluster head at the initial stage of clustering, which reduces the computation and communication overhead. The second is to elect that node to be a cluster head, which retains its neighbourhood for a longer time period which maintains cluster stability. The third is to retaliate against a selfish node in case of any misbehaviour or non-cooperation using the punishment algorithm and enforcing it to behave normally rather than simply blacklisting that node. The simulation results demonstrate the efficacy of the proposed algorithm compared with the other existing algorithms in terms of different performance metrics.

Keywords: ad-hoc networks; clustering; cluster head; stability factor; selfishness factor; punishment factor.

DOI: 10.1504/IJWMC.2018.091144

International Journal of Wireless and Mobile Computing, 2018 Vol.14 No.2, pp.164 - 177

Accepted: 02 Jan 2018
Published online: 06 Apr 2018 *

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