In Wireless Sensor Network (WSN), clustering is considered as the primary model to prolong the life expectancy. Nevertheless, in WSN Cluster Head Selection (CHS) still residue the main confront on regarding energy stabilization. In this paper, the Adaptive Cuckoo Search and Squirrel Search Algorithm (ACS-SS) to simulate the optimal CHS model is presented. Here, the main aim is to choose the Cluster Head (CH) optimally by concentrating on the stabilization of energy, reduction of delay and reduction of distance among nodes. The proposed model is the hybridization of the Adaptive Cuckoo Search and Squirrel Search Algorithm to achieve optimal performance. Subsequent to the experimentation, the performance of the proposed technique compares with the existing techniques like the Genetic Algorithm (GA), Artificial Bee Colony (ABC), Group Search Optimization (GSO), and Firefly (FF) based CHS. Moreover, the performance analysis of the proposed technique seems to evaluate the energy efficiency, network lifetime, and statistics of dead nodes. The experimentation results exhibit the proposed CHS model is high effectual to extend the lifespan of the network.
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