Adaptive dynamic multi‐hop technique for clustering protocol in wireless sensor networks assisted‐Internet of Things applications

Abstract

Recent technological advancements in wireless communication technologies and networking have enabled the Internet of Things (IoT) systems’ designing. Since the wireless sensor networks refer to networks of embedded IoT devices to provide sensing services with limited energy and storage resources, the energy consumption is an important requirement for communication in IoT applications. Clustering algorithms have been investigated as a technique for energy conservation in networks with scarce resources. The appropriate cluster head balances the load in the network, lowering energy consumption and extending the network lifetime. An energy-saving solution is proposed based on an effective cluster head selection method that assigns cluster heads to nodes based on which have the highest energy level. The proposed algorithm is called Adaptive Dynamic Multi-Hop-Low Energy Adaptive Clustering Hierarchy (ADMH-LEACH). The proposed algorithm is intended for IoT applications in the oil and gas (O&G) industry. The deployment of the adopted algorithm leads to improved field communication, lower maintenance costs, real-time monitoring, digital oil field infrastructure, lower power consumption, increased asset safety and protection, and thus increased productivity. The ADMH-LEACH is based on a variety of variables, including initial energy, residual energy, and energy consumed per round, in order to meet quality-of-service constraints by following service level agreements for O&G IoT applications. The simulation results show that the proposed algorithm improves network reliability, network lifetime, and load balance significantly in comparison to current algorithms.