Probabilistic-Based Energy-Efficient Single-Hop Clustering Technique for Sensor Networks

Energy efficiency has a vigorous extent of research in sensor networks. There are a widespread investigation and research activities going towards this path, and present techniques are not yet successful, to completely address this challenge due to its inadequate precision and relevance. As a prior work, this research also put emphasis on improving the sensor network lifetime based on the residual energy levels of cluster heads (CHs). In this research, instead of changing CHs for dynamic clustering at every round, we intend an optimal CH threshold function and an energy threshold function to postulate the dynamicity of CH based on the current energy intensities, thus enhancing the sensor network lifetime. Extensive simulation using NS-2 and result analysis have proved that our proposed technique reduces the energy consumption and maximizes the network lifetime when compared with protocols from the literature.