Metaheuristic-enabled shortest path selection for iot-based wireless sensor network

Abstract

IoT is defined as a pervasive and global network that aids and provides the system for monitoring and controlling the physical world through the processing and analysis of generated data by IoT sensor devices. Wireless sensor networks (WSNs) are comprised of a large number of nodes distributed in a vast region. Routing protocols are responsible for the development and the management of network routes. This paper intends to propose an optimized routing model for selecting the optimal shortest path in IoT-based WSN. More particularly, a dragonfly algorithm with Brownian motion (DABR) model is introduced to select the optimal route by taking into consideration of certain constraints such as (i) delay (ii) distance (iii) packet drop rate (PDR) and (iv) energy. Finally, the performance of the proposed work is compared with the conventional models to demonstrate the superior performance.