Design and implementation of energy-efficient hybrid data aggregation in heterogeneous wireless sensor network

Abstract

Heterogeneous wireless sensor network (HWSN) is a trending technology in both the industrial and academic sectors, consisting of a large number of interconnected sensors. However, higher energy consumption and delay are significant drawbacks of this technology in applications such as military, healthcare, and industrial automation. The main objective of this research is to enhance the energy efficiency of HWSN using a clustering technique. In this article, a novel approach, namely power optimization and hybrid data aggregation (POHDA), is proposed to address these challenges in HWSN. POHDA-HWSN focuses on power optimization and congestion avoidance through effective CH selection using hybrid data aggregation based on parameters such as residual energy, distance, mobility, threshold value of the node, and latency. By weight-based effective cluster head (CH) selection, the energy consumption, end-to-end delay, and overhead during communication are reduced in this network. The POHDA-HWSN approach considers specific parameters to compare the results and outcomes with earlier research such as HCCS-WSN, FMCA-WSN, and APCC-WSN. The results prove that the proposed POHDA-HWSN approach achieves higher energy efficiency and delivery ratio.