Open AccessAn Enhanced-Node Feature Based Clustering Algorithm for MANET (Mobile Ad-hoc Network)
Author(s) -
Sandeep Monga,
Dr J.L Rana,
Deb Agarwal
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d8727.118419
Subject(s) - cluster analysis , computer science , mobile ad hoc network , node (physics) , algorithm , wireless ad hoc network , computer network , data mining , artificial intelligence , engineering , telecommunications , structural engineering , network packet , wireless
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).