Economic Transformations in Urban Industries during Energy Transition: Novel Tradeoff Technique for Balancing Energy Consumption

Abstract

Mobile terminal devices are becoming more prevalent owing to the growth of the Internet of Things (IoT). Mobile device terminals generate large amounts of information, which results in increased power consumption (PC) and delays. Nevertheless, the short delay often leads to increased PC. The present study proposes a tradeoff technique for balancing PC and delay so as to achieve optimum PC and delay in a smart grid as a very large scale system. The first objective is to explain how a delay threshold reduces delay in the market. Following that, the delay and PC of the mobile terminal layer, fog node layer, and cloud server layer with lineup view are described. The energy optimization issue is solved via computing the optimum workload of the layers using nonlinear programming. A cloud-fog solidarity planning scheme has been modelled for reducing PC. In addition, it is possible to create an algorithm that completes work when the nodes depart. The experimental outcomes show a reduction of about 22% in energy use, as well as a reduction in delay of 12.5% over the prime come prime served method. Integrating economic considerations, the study reveals a cloud-fog solidarity planning scheme aimed at dropping energy consumption and optimizing delay, resulting in a 22% decrease in energy use and a 12.5% reduction in delay compared to the prime come prime served method in the context of urban industries' energy transition.