A novel energy harvesting with middle-order weighted probability (EHMoWP) for performance improvement in wireless sensor network (WSN)

Abstract

Wireless sensor network (WSN) has been a promising technology and widely involved in environmental monitoring. The limited energy supply associated with WSNs impacts the lifetime of the network and the energy constraints make it difficult for sensor nodes to harvest environmental energy. This drawback on the performance of WSN is improved through routing and clustering techniques for environmental energy harvesting and termed as harvesting wireless sensor network (EH-WSN). As a result of the unique characteristics of EH-WSN, the performance of typical clustering and routing protocols of WSN are ineffective in EH-WSN. A novel energy harvesting middle-order weighted probability (EHMoWP) is proposed in this paper for the static and dynamic operation of WSN nodes. The proposed EHMoWP approach is based on the integration of cluster head selection and routing, with the utilization of a distributed–centralized approach which cogitates the energy of nodes, harvested energy, clustering process, and neighbor nodes. Simulation outcomes showed that this proposed EHMoWP outperforms significantly the conventional techniques concerning residual energy and the number of alive and dead nodes. The proposed EHMoWP exhibits almost 10% higher residual energy with improved network lifetime which is measured in terms of alive node and dead node count. Based on the analysis of dead node and alive node estimation, it was observed that the number of alive nodes was 10% higher and the number of dead nodes was 10% fewer than in the conventional technique. This is because the proposed EHMoWP exhibits 2 dead nodes less and 2 alive nodes higher than the existing technique.