Shuffled Shepherd Squirrel Optimization and Fractional LMS Model for In-Network Aggregation in Wireless Sensor Network

Abstract

The wireless sensor network (WSN) is commonly based on small node collaboration. These nodes are specified by wireless communication, low price, and energy consumption. Moreover, the WSN can be utilized to compute pressure, temperature, as well as monitoring health, military supervision, and so on. A variety of WSN applications need to gather data from sensor nodes based on sink. In this paper, shuffled shepherd squirrel optimization (SSSOA) technique is devised for in-network aggregation in WSN. Here, the path is formulated from source node to destination through routing process, and source node broadcasts a packet concurrently to destination. The WSN is initiated, and the suitable cluster head (CH) is selected from all nodes. Consequently, CH is selected based on the developed shuffled shepherd squirrel optimization (SSSOA) method.