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Performance Analysis of Malicious Node Detection and Elimination Using Clustering Approach on MANET

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DOI: 10.4236/cs.2016.76064    1,723 Downloads   2,381 Views   Citations

ABSTRACT

Mobile Ad hoc Network (MANET) is a significant concept of wireless networks which comprises of thousands of nodes that are mobile as well as autonomous and they do not requires any existing network infrastructure. The autonomous nodes can freely and randomly move within the network which can create temporary dynamic network and these networks can change their topology frequently. The security is the primary issue in MANET which degrades the network performance significantly. In this paper, cluster based malicious node detection methodology is proposed to detect and remove the malicious nodes. Each node within the cluster gets the cluster key from the cluster head and this key is used for the data transaction between cluster head and node. The cluster head checks this key for every data transaction from node and match with their cluster table. If match is valid, and then only it will recognize that this node is belongs to this cluster, otherwise it is decided as malicious node. This paper also discusses the detection of link failure due to the presence of malicious node by determining the gain of each link in the network. The performance of the proposed method is analyzed using packet delivery ratio, network life time, and throughput and energy consumption. The proposed malicious node detection system is compared with the conventional techniques as OEERP (Optimized energy efficient routing protocol), LEACH (Low energy adaptive clustering hierarchy), DRINA (Data routing for In-network aggregation) and BCDCP (Base station controlled dynamic clustering protocol).

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Gopalakrishnan, S. and Kumar, P. (2016) Performance Analysis of Malicious Node Detection and Elimination Using Clustering Approach on MANET. Circuits and Systems, 7, 748-758. doi: 10.4236/cs.2016.76064.

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