A Multi-objective Routing Optimization Using Swarm Intelligence in IoT Networks

Abstract

Internet of Things (IoT) network devices, are embedded wireless sensor nodes, constrained with limited battery capacity, storage and processing power. Hence, the available resources have to be utilized efficiently during the process like sensing, computing and communication. This creates a need for an optimized routing algorithm which should reduce the resource consumption like battery power to extend the network lifetime, and also we should consider the other network requirements like delay, throughput and packet delivery ratio. Here, a multi-objective routing optimization algorithm BFOA-R is proposed, based on group foraging behavior of E. coli and M. xanthus bacteria. The primary objective of the proposed routing is to reduce energy consumption during routing and maximize network life. Existing, particle multi-swarm optimization is used as a benchmarking method to evaluate the performance of BFOA-R.