Analysis of Efficient Task Scheduling Algorithms in Fog Computing Environment

The evolution of computing paradigms, including parallel, distributed, grid, and cloud computing (CC), has led to the widespread adoption of CC due to its features like on-demand resource allocation, flexible pricing, and service provisioning through models such as IaaS, PaaS, and SaaS. However, the centralized nature of most cloud data centers introduces challenges like latency and inefficiencies due to the distance between devices and the cloud. This study shows that Edge computing has emerged as a solution by enabling localized data processing at the network's edge, reducing latency and reliance on centralized systems. Unlike CC, edge computing focuses on end devices. In this paper, Fog computing as an upcoming technology further extends the capabilities of CC by integrating edge and core network functionalities, providing a seamless bridge between edge and cloud paradigms to enhance computational performance and efficiency.