Using Heterogeneous Cloud Computing to Manage Resources in Sustainable Cyber-Physical Systems

A significant increase in heterogeneous distributed computing has allowed for significant advancements in cyber physical systems (CPS). An additional strategy for enhancing system sustainability is to combine CPS with heterogeneous cloud computing. However, there are still certain difficulties with resource management in cloud systems, such as work allocation in heterogeneous clouds and Web server capacity limitations. Service delays are frequently caused by the erratic demand for services, which is embarrassing for the businesses' ability to compete. This article tackles the NP-hard problem of job assignment in heterogeneous clouds, which has been shown. The suggested method is known as the Smart Cloud-based Optimizing Workload (SCOW) Model, which assigns jobs to heterogeneous clouds using forecast cloud capacity and sustainable parameters. We provide a few strategies, such as the Workload Resource Minimization (WRM), Smart Task Assignment (STA), and Task Mapping Algorithm, to achieve the optimization target (TMA). Our experimental analyses have looked at how well the suggested strategy performs.