Abstract
In the realm of enhancing security management systems within Wireless Sensor Network (WSNs) for Big Data applications, the role of optimization algorithms is pivotal. This chapter delves into the utilization of Gray Wolf Optimization (GWO) as a fundamental tool to achieve efficient resource allocation, node placement optimization, and the enhancement of data transmission efficiency within WSNs. A detailed exploration of the mathematical foundations of GWO is provided to foster a comprehensive understanding of its application in security enhancement.
 In this paper Gray Wolf Optimization (GWO) is a nature-inspired metaheuristic algorithm presented that draws inspiration from the social behavior of gray wolves in the wild. In our study, GWO is employed to optimize various parameters that significantly impact the efficiency and effectiveness of WSNs.
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