Efficient Bio-Inspired Routing Algorithm for IoT

Abstract

Wireless Sensor Networks (WSNs) is a fundamental portion of different applications. One of those applications is Internet of Things (IoT). IoT sensor-based applications have become one of the most used applications in various fields. Whereas the surrounding data is sensed by sensor nodes and transmitted to its destination. Sensors are mostly attached with a limited source of power like batteries. Therefore, finding an efficient routing algorithm to save energy has become a must. In this paper, we present a new routing algorithm that is aimed to elongate the network lifetime and conserve the energy of sensor nodes. A hybrid intelligent algorithm is proposed. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm are used in our proposed algorithm. Whereas GA is used to select the efficient cluster head. The fitness function of GA considers distance and energy parameters while selecting the cluster heads. Then, ACO is used for data transmission. Furthermore, the distance and energy parameters are considered in ACO while choosing the best path to transmit data from a cluster head to the base station. The performance of the proposed hybrid routing algorithm was compared with Enhanced LEACH algorithm and GA-PSO algorithm. The results of the comparison show that the network lifetime of our proposed hybrid routing algorithm lives 3.1% longer than GA-PSO and 21.2% longer than Enhanced LEACH. This means that our proposed algorithm saves the nodes’ energy and prolongs the network lifetime more than GA-PSO and Enhanced LEACH algorithms.