An Enhanced-Node Feature Based Clustering Algorithm for MANET (Mobile Ad-hoc Network)
Sandeep Monga1, J.L Rana2, Jitendra Agarwal3
1Sandeep Monga*,School of Information Technology, RGPV, Bhopal India.
2Dr J.L Rana, Computer Science & Enginneering, MANIT, Bhopal, India.
3Dr Jitendra Agarwal, School of Information Technology, RGPV, Bhopal India.

Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 5534-5538 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8727118419/2019©BEIESP | DOI: 10.35940/ijrte.D8727.118419

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Abstract: In mobile Ad-hoc Network cluster stability is considered as a very serious issue. Due to the frequent failure of the network it may reduce the stability of the cluster. In re-clustering and re-election of Cluster Head (CH) higher energy is required, which ultimately reduces the overall network performance. To resolve the cluster stability problems, Weight Based Clustering algorithm is used often. In this paper, a new weight based algorithm called Enhanced-Node Feature Based Clustering Algorithm (ENFBCA) is proposed, which uses the following parameters for cluster head selection process mainly Link Estimate Time, Degree of the node, Node Closeness, Residual Energy & Trust value. This algorithm reduces the End-to-End delay, enhances the Network Lifetime and improves the quality of service (QOS) in MANETs. Simulation results show that Enhanced-Node Feature Based Clustering Algorithm (ENFBCA) performs better in comparison to Node Quality Clustering Algorithm (NQCA) and Weight Based Clustering algorithm (WCA).
Keywords: Clustering, Cluster Head, MANET, WCA.
Scope of the Article: Clustering.