Maximum Energy Productivity for Concurrent Wireless Data and Power Shifting-Enabled IoT Network with Energy Coordination

Abstract

The online phase may be successfully extended by simultaneous wireless data, internet of things (IoT) components, and sophisticated technologies. The development support base station is developed to accomplish the exchange of renewable electricity to manage the volatility of power generation by the hybrid access points. In this research, we jointly investigate the cooperative SWIPT-enabled IoT systems. While maximizing the program's energy consumption, we must also adhere to maximize the transmission limits, thermoelectric generator restrictions, and customer quality of service (QoS) requirements. We collaborate to find solutions to the challenges of power-sharing, period shifting, and ecological collaboration. The incessant algorithm is employed to address the load distribution and duration swapping problems, the matching algorithm is employed to fix the cooperation agreement issue, and since this trouble is a nonlinear optimization issue, it is challenging to address directly. Instead, we are using the interchanging differential technique. The outcomes of the simulations demonstrate that the suggested algorithm performs with a considerable advantage in terms of energy conservation compared to the comparative method. Also, it has been shown that using energy collaboration technologies can reduce the amount of power a system uses and make it run better.