Fog Node Selection and Task Scheduling in Fog Computing Environment: A Review
Bhupendra Panchal, Preeti Saxena · 2025
Fog Computing is an emerging field of cloud computing, resides between cloud and Internet of Things (IoT) devices. IoT consists of sensors, cameras, actuators, and other smart devices. IoT devices generate latency-sensitive tasks in real-time environment and forward them at fog layer. Fog layer analyses the incoming tasks, schedule them, and allocate resources for their processing. In delayed-sensitive applications, task scheduling and their allocation are much complex as they require quick responses, and real-time decisions. Additionally, frequent node failures are common due to diverse characteristics of fog computing. It becomes more crucial and essential to identify reliable fog nodes at fog layer for further computations. This study presents a systematic review of existing fog node selection methods with consideration of different selection parameters. Furthermore, the study reviews existing scheduling and allocation methods under heuristic, meta-heuristic, optimization, and machine learning approaches. The study reviews existing techniques with consideration of delay, energy usage, costs, network usage, and reliability. As per the comparative analysis, the study identified reliability as most significant issues in the existing approaches. Finally, the study provides future research suggestions to improve the reliability in fog environment for improving QoS.