Hybrid cat and mouse-based dolphin swarm optimization strategy for intelligent routing in wireless sensor network applicable for iot applications

Abstract

Wireless Sensor Network (WSN), a group of small sensor nodes with lower energy states are widely used for the purpose of communication. While designing the WSN system, Energy Efficiency (EE) and energy consumption have become essential parameters in the past few decades. Moreover, several techniques are adapted to improve the EE and minimize the energy consumption for attaining better lifetime in WSN. Also, the conventional technique faces challenges in terms of Quality of Service (QoS). There is a need to choose the cluster Head (CH) for every cluster node to provide better QoS service. In addition to this, the selection of the most relevant CH is the WSN sensor node becomes a challenging issue. In this research work, the three-stage selection process like CH selection, Clone CH (CCH) selection, and also the selection of Direct Nodes (DN) in the WSN sensor hubs that are located among source and sink to offer better services in WSN. For this CH selection, a Hybrid Cat and Mouse with Dolphin Swarm Optimization (HCM-DSO) Algorithm is introduced in this paper. Here, the multi-objective constraints of QoS like the sensor hub’s residual energy, latency, throughput, Euclidean distance between the sensor hubs, and network’s average energy, intra-cluster distance, and inter-cluster distance for determining an efficient QoS routing scheme are accomplished by developed HCM-DSO algorithm. Moreover, the extensive experiments are carried out with different scenarios. The outcome of experimentation shows the effectiveness of the suggested model for enhancing the lifetime of the network when compared with existing protocols in homogenous conditions.