M2M Leach-Based Cross-Layer Protocol for Enhancing Energy Efficiency in Wireless Sensor Networks



A Wireless Sensor Network (WSN) comprises sensor nodes functioning collectively to monitor diverse environmental parameters for a range of applications. Prolonged operation of these networks is crucial to fulfill their intended objectives. The Low Energy Adaptive Clustering Protocol (LEACH) is a self-organizing technique designed to counteract the limited lifespan of such networks. This protocol has been adapted with various parameters and directives to enhance the WSN’s longevity. However, the escalating demand for information coupled with an increased deployment of sensor nodes per unit area presents challenges to WSN performance in terms of longevity and energy utilization.

This study addresses the issues arising from a large number of nodes within an area and a high density of nodes per cluster, aiming to optimize energy usage and distribution. The proposed approach involves the adjustment of contention window (CW) parameters to facilitate efficient communication within clusters. The determination of an optimal number of clusters is based on the density of deployed nodes and neighbor counts. The method involves the segmentation of nodes within the coverage area into clusters. These segmented nodes collect field data, forwarding it to their respective cluster heads, which subsequently relay the data upwards through the hierarchy until reaching the sink.

Intra-cluster communication primarily occurs between nodes within a cluster and their corresponding cluster heads. While conventional intra-cluster communication relies on direct transmission, this study introduces the concept of Contention Window LEACH (CW_LEACH) to enhance performance. CW_LEACH demonstrates superior performance and extended network lifespan. By considering the active number of nodes during CW selection, optimal contention window adjustment effectively utilizes channel resources, mitigating collisions and enhancing channel efficiency.

Simulations conducted in MATLAB reveal a 16% increase in the total number of communication rounds and 2400 instances of successful transmission, showcasing enhanced energy maximization through judicious channel utilization, reduced idle listening, and minimized overhearing. The proposed technique holds promise for applications in the Internet of Things (IoT) and 5G-enabled devices.

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