Impact of Finding Selfish Nodes in Manet
V Anandkumar1, Kalaiarasan T R2, Ratheesh Kumar A M3
1Dr Anandkumar V, Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore, India.
2Kalaiarasan T R, Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore, India.
3Ratheeshkumar A M, Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore, India.
Manuscript received on 06 August 2019 | Revised Manuscript received on 12 August 2019 | Manuscript published on 30 August 2019 | PP: 4141-4144 | Volume-8 Issue-10, August 2019 | Retrieval Number: J98670881019/2019©BEIESP | DOI: 10.35940/ijitee.J9867.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The nodes that operate in the self-organized functions of Mobile Ad hoc Networks (MANETs) participate in the network but increase the energy and resources consumption. As some nodes are non-cooperative with others in the network, it is necessary that those nodes have to be removed. Active researches are conducted to deal with those selfish nodes that are non-cooperative. Methods/ Statistics: Our paper analyzes by comparing the 2ACK method simulated using hash chain one-way scheme with digital signature and DSR methods. Findings: The simulation analysis suggest that a considerable percentage of packets delivered of 2ACK method is greater when compared with Digital signature or any other DSR methods but has the capability in finding a considerable number of selfish nodes present in the network. Applications/ Improvements: the 2ACK scheme can be used to control the network overhead using the authentication schemes and can be enhanced to monitor the video traffic can be monitored. Keywords: MANET, Misbehaving Nodes, Digital Signature, MAC Layer, One Way Hash Chain.
Scope of the Article: Digital Signal Processing Theory