QoE based Multi Criteria Decision Making Approaches for Resource Allocation and Scheduling in FOG Computing

Abstract

In order to address the demands of contemporary technologies like the Internet of Things (IoT), Artificial Intelligence (AI), 5G, and more similar elements, Fog computing is working as an extended platform of cloud computing. The advancement of numerous application scenarios, including healthcare, smart cities, transportation, entertainment, and agriculture, which have a substantial impact on people's daily lives, is being facilitated by the IoT paradigm. These apps must have the processing and storage power to handle the massive volume of data prepared by IoT devices. IoT devices cannot effectively process and store significant amounts of data due to their inherent resource limitations. Therefore, IoT devices need substitute resources to ensure the efficient execution of their diverse applications, some of which may be computation-intensive or latency-sensitive. One of the potential resource suppliers for IoT devices is the cloud. Although it impacts the amount of time IoT devices are actively using energy. Subsequently, the usage of smart apps that respond instantly has increased significantly along with the use of IoT-enabled devices.