CCABC: Cyclic Cellular Automata Based Clustering For Energy Conservation in Sensor Networks

TL;DR

This paper introduces CCABC, a clustering method based on modified cyclic cellular automata, to enhance energy conservation in wireless sensor networks by optimizing cluster formation and reducing communication costs.

Contribution

It presents a novel clustering scheme using mCCA that effectively conserves energy without sacrificing network coverage in sensor networks.

Findings

CCABC reduces energy consumption compared to existing schemes.

The scheme maintains network coverage while optimizing cluster size.

Simulation results confirm improved reliability and efficiency.

Abstract

Sensor network has been recognized as the most significant technology for next century. Despites of its potential application, wireless sensor network encounters resource restriction such as low power, reduced bandwidth and specially limited power sources. This work proposes an efficient technique for the conservation of energy in a wireless sensor network (WSN) by forming an effective cluster of the network nodes distributed over a wide range of geographical area. The clustering scheme is developed around a specified class of cellular automata (CA) referred to as the modified cyclic cellular automata (mCCA). It sets a number of nodes in stand-by mode at an instance of time without compromising the area of network coverage and thereby conserves the battery power. The proposed scheme also determines an effective cluster size where the inter-cluster and intra-cluster communication cost is minimum. The simulation results establish that the cyclic cellular automata based clustering for energy conservation in sensor networks (CCABC) is more reliable than the existing schemes where clustering and CA based energy saving technique is used.