Title: Optimisation of energy efficient cellular learning automata algorithm for heterogeneous wireless sensor networks

Authors: C.P. Subha; S. Malarkkan

Addresses: Department of Electronics and Communication Engineering, Sathyabama University, Rajiv Gandhi Road, Jeppiaar Nagar, Chennai, Tamil Nadu 600119, India ' Manakula Vinayagar Institute of Technology, Kalitheerthalkuppam, Puducherry – 605107, India

Abstract: Wireless sensor networks is an effective sensing network consisting of a large number of small sensors and small embedded devices each with sensing, computation and communication capabilities for gathering data in various environments. Energy consumption is considered to be an important issue in the design of wireless sensor networks. To overcome the above limitation, efficient method like cellular learning automata (CLA) and heterogeneous-hybrid energy efficient distributed (H-HEED) technique have been used in distributed dynamic clustering networks. The existing method will be the cellular learning automata in which cluster heads will be selected through several stages by considering various parameters with homogeneous nodes. The proposed method selects the cluster head in a similar way and based on the residual energy of the nodes with heterogenous nodes. Their performance is observed using NS2 simulator and comparison has been made to find the best efficient method.

Keywords: cellular automata; learning automata; heterogeneous-hybrid energy efficient distributed; H-HEED; clustering; wireless sensor networks; WSNs; dynamic; irregular cellular learning automata; distributed dynamic clustering; residual energy.

DOI: 10.1504/IJNVO.2017.085526

International Journal of Networking and Virtual Organisations, 2017 Vol.17 No.2/3, pp.170 - 183

Received: 29 Mar 2016
Accepted: 16 May 2016

Published online: 30 Jul 2017 *

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