CSRP Protocol for High Accuracy Performance in Wireless Sensor Networks

In recent years, Wireless Sensor Network (WSN) has played a broad role in many vital applications that are used to monitor environmental and physical events. One of the major issues in WSN is the overlapping region of sensing bands, which occurs due to densely and randomly deployed nodes in the target environment. The data aggregation technique is used as a solution that processes overlapping regions. This technique manages and redirects these data to the sink node through a multi-hop network. Therefore, the data transmission number and the duration toward the sink node are reduced, which fixes the overlapping region issue. However, using data aggregation techniques limited network performance due to energy consumption. The objective of this paper is to address this limitation by employing intelligent algorithms to enhance the operation strategies of data aggregation techniques. A protocol based on the Hierarchical Agglomerative Clustering (HAC), Self-Organized Map (SOM), and Enhanced Radial Basis Function (ERBF) neural network is proposed in order to accomplish this goal. The clustered SOM and RBF-based Intelligent Protocol (CSRP) is the name of this proposed protocol. When compared to pertinent recent studies, the suggested protocol produced the best results in terms of the accuracy of the data arriving at the base station.