A high-scalability and low-latency cluster-based routing protocol in time-sensitive WSNs using genetic algorithm

Abstract

Wireless Sensor Networks (WSNs) play a critical role in data transmission and reception across a multitude of applications. A primary challenge in WSNs is managing scalability and latency due to the deployment of numerous sensor nodes, each with limited memory and energy resources. Moreover, understanding the randomness in node distribution across the WSN is complex. A commonly employed technique to address this issue is clustering, which groups distributed nodes within the network. A node with high energy, preferably located near the cluster's center, is selected as the cluster head to enhance latency. This paper primarily focuses on developing an efficient routing protocol to improve the scalability of WSNs. An ideal routing protocol should adapt to network topology changes. In this proposal, a Genetic Algorithm-based routing mechanism, the Cluster-based Genetic Routing Protocol (CGRP), is established. CGRP is particularly suitable for highly distributed and rapidly expanding networks, performing well even with an increase in workload. A mathematical evaluation is conducted to elucidate the scalability of the network. To demonstrate CGRP's efficiency, it was compared with various conventional state-of-the-art routing algorithms. Experimental results indicate that CGRP outperforms these algorithms, achieving lower latency and proving robust in highly scalable WSNs.