Conventional wireless sensor networks (WSNs) have constrained sensing, computation, and wireless communication characteristics of an enormous number of randomly placed nodes [1][2]. Since physical resources are the foundation of network architecture, developing an effective routing strategy is essential to obtaining the lowest possible resource consumption [3][4]. It is believed that conventional WSNs are designed for specific applications, which makes it quite challenging to respond to events and modify high-level network policy. Therefore, these high-level policies must be specified in distributed low-level configurations [5][6]. Even though there are numerous challenges, like sleep methods and different forms of data fusion that may arise from weak connections or significant energy waste, these issues cannot be resolved in an ossified network architecture. A large-scale WSN management system must employ several methodologies to provide system self-healing and maintainability. The system must have the capability to modify the parameters based on variables, such as a decrease in service quality when the energy resource becomes inadequate. This is a challenge in the current WSN design since all control and data packets must be routed across a restricted network band.