Fuzzy spider monkey optimization routing protocol to balance energy consumption in heterogeneous wireless sensor networks

Abstract

Wireless sensor network (WSN) nodes have high computation limitations, limited communication capabilities, and limited power resources because of the difficulty or impossibility of replacing or recharging the sensor battery. Energy consumption in nodes is a critical issue to consider while developing WSNs. Many routing protocols are proposed for energy conservation as an important goal for improvement. Nonetheless, just delivering energy is not enough to prolong the life of a WSN. Unbalanced energy depletion is a significant problem in WSNs, often resulting in network splits and a reduction in network lifetime, as well as performance retrogression. This article, therefore, proposes a robust protocol called the fuzzy spider monkey optimization routing protocol (FSMORP) to determine the best data path routing for heterogeneous WSNs (HWSNs). In this case, an FSMORP computes the best path across the cluster heads from a sensor to the sink. This work uses the clustering method to organize heterogeneous nodes in HWSNs. The simulation result indicates that the FSMORP considerably enhances data latency reduction, energy balancing, and lifetime maximization for the network.