Predicted Fitness Based Clustering Algorithm for Manets
C.Kalaiselvi1, S.Palaniammal2

1C.Kalaiselvi, Department of Mathematics, Sri Krishna College of Technology, Coimbatore, Tamilnadu, India.
2Dr. S. Palaniammal, Principal, Sri Krishna Adithya College of arts and Science. Coimbatore, Tamilnadu, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 488-494 | Volume-8 Issue-6, August 2019. | Retrieval Number: E7907068519/2019©BEIESP | DOI: 10.35940/ijeat.E7907.088619
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Abstract: Secure data delivery, mobility, link lifetime, energy consumption and delay are the most important parameters to be highly concentrated in the self-organised network named manets. Where in Manets the nodes move unpredictably in any direction with restricted battery life, resulting in frequent change in topology and due to mobility the trust in packet delivery will suffer inside the network. These constraints are studied broadly to ensure the secured data delivery and the lifetime of such networks. In this paper we propose a PFCA(Predicted fitness based clustering) algorithm using fitness value. The cluster heads are selected based on the fitness value of the nodes. Whereas the fitness value is calculated using the trust value, link lifetime for different type of node mobility and energy consumed and the clusters are formed using the PFCA clustering algorithm. The proposed PFC algorithm is experimented in the NS-2 network simulator and the results are compared with the existing PSO-clustering algorithm. The results show the effectiveness of our proposed algorithm in terms of network overhead, average number of clusters formed, average number of re-clustering required, delay and packet delivery ratio.
Keywords: Clustering, Fitness, Link reliability, Mobile adhoc networks(MANETS), Trust.