Exponential Reliability Coefficient based Reputation Mechanism for isolating selfish nodes in MANETs

被引:13
|
作者
Sengathir, J. [1 ]
Manoharan, R. [1 ]
机构
[1] Pondicherry Engn Coll, ECR, Dept Comp Sci & Engn, Pondicherry 605014, India
关键词
Selfish nodes; Exponential weighted moving average; Residual power; Power drain rate; Exponential Reliability Coefficient;
D O I
10.1016/j.eij.2015.05.003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In mobile ad hoc networks, cooperation among active mobile nodes is considered to play a vital role in reliable transmission of data. But, the selfish mobile nodes present in an ad hoc environment refuse to forward neighbouring nodes' packet for conserving its own energy. This intentional selfish behaviour drastically reduces the degree of cooperation maintained between the mobile nodes. Hence, a need arises for devising an effective mechanism which incorporates both energy efficiency and reputation into account for mitigating selfish behaviour in MANETs. In this paper, we propose an Exponential Reliability Coefficient based reputation Mechanism (ERCRM) which isolates the selfish nodes from the routing path based on Exponential Reliability Coefficient (ExRC). This reliability coefficient manipulated through exponential failure rate based on moving average method highlights the most recent past behaviour of the mobile nodes for quantifying its genuineness. From the simulation results, it is evident that, the proposed ERCRM approach outperforms the existing Packet Conservation Monitoring Algorithm (PCMA) and Spilt Half Reliability Coefficient based Mathematical Model (SHRCM) in terms of performance evaluation metrics such as packet delivery ratio, throughput, total overhead and control overhead. Further, this ERCRM mechanism has a successful rate of 28% in isolating the selfish nodes from the routing path. Furthermore, it also aids in framing the exponential threshold point of detection as 0.4, where a maximum number of selfish nodes are identified when compared to the existing models available in the literature. (C) 2015 Production and hosting by Elsevier B.V. on behalf of Faculty of Computers and Information, Cairo University.
引用
收藏
页码:231 / 241
页数:11
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