An enhanced cluster head selection criterion of LEACH in wireless sensor networks

Abstract

Recent advances in wireless sensor network technology have enabled the implementation of a variety of reliable, and distributed monitoring and controlling systems used in several sectors such as environment, healthcare, civil, and military. This has in turn led to the development of many of their features and optimizations for the purpose of efficiency, reliability, and scalability but with the key constraint of limited power supply sensor nodes. Several efficient power control and management schemes have been explored to keep the sensor nodes in the network operational for a long period in order to increase network lifetime. One of the more promising techniques is based on a hierarchical architecture or cluster-based routing that can be employed to enable the sensor networks to be deployed in a large-scale area. Low Energy Adaptive Clustering Hierarchy (LEACH) is a hierarchical scheme that provides simplicity and distributed operations with power-aware clustering. It is also widely used as a baseline for several further LEACH derivations. This research comparatively investigates the performance of LEACH's recent optimizations, especially the clustering criteria for selecting a proper set of cluster heads. To further enhance the probability criteria of the selected nodes, this research also recommends the modification of using adaptive moving window average and selection probability into an energy factor during the threshold selection stage. The results of this modification show an improvement of overall system energy usage.