Optimisation of the hybrid grey wolf method in cluster-based wireless sensor network using edge computing Online publication date: Mon, 19-Feb-2024
by Ashok Kumar Rai; Rakesh Kumar
International Journal of Grid and Utility Computing (IJGUC), Vol. 15, No. 1, 2024
Abstract: Wireless Sensor Networks (WSNs) cover most of the secure data transfer applications and play a significant role in the IoT for primary data collection, which needs energy-efficient data transfer and improved network lifetime. The major challenge for these protocols is setting up optimum clusters and Cluster Head (CH) formation for efficient operation. WSNs have a critical role in parallel computation in which resources can be assigned to the sub-task and equalise the load, which improves the network lifetime. This paper uses the Grey Wolf Optimisation (GWO) algorithm in the proposed work by observing two variables, i.e., Residual Energy (RE) and node distance (DS) from Base Station (BS) that visualised and analysed the GWO under variable parameters in WSN. This approach identifies the most suitable node from all normal nodes for the selection of CH. The outcome demonstrates that using GWO improved the performance of the proposed model.
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