Analyzing Resource Allocation Methods in Fog Computing for Task Scehduling: A Study of Heuristic and Meta-Heuristic Approaches

With the remarkable improvement of the Internet, there has been an important flow in technologies like cloud and fog computing. Moreover, it is important to identify the associated issues related to resource allocation and deployment in these technologies. Despite the rapid development of cloud computing (CC), several limitations persist due to inherent features like unreliable delays, limited mobility, and limited support. Fog computing (FC), on the other hand, includes taking the central CC resources nearby to the network edge. It aims to overcome the limitations faced by CC by providing a more distributed method compared to its centralized behavior. The disparities between compute-intensive uses and resource-constrained devices challenge the complete system’s performance. Task scheduling (TS) is important in identifying logical inconsistencies in fog technology. With the proliferation of the IoT, efficiently allocating resources to clients upon request becomes a highly challenging task in fog technology. Different authors survey several methods, which are analyzed in brief. Lastly, a study is made by comparing the demerits of each technique, and recommendations are defined for improved TS and RA in fog. In this article, some heuristic and metaheuristic methods are studied, and the hyper-heuristic scheduling (HHS) method is defined to explore the best distribution with minimum execution time. The implemented technique has enhancements in energy, execution time, etc.