Adaptive load-balancing multi-criteria scheduling algorithm for fog computing systems
Shahid Sultan Hajam, Iraq Ahmad Reshi, Irfan Rasool, Afaq Alam Khan, Mohammad Ahsan · International Journal of Computers and Applications · 2025
Fog nodes with multi-processor provides an efficient framework for processing time-sensitive tasks. However, scheduling the tasks in such systems involves challenges: distribution of tasks evenly among fog nodes and also among the processors within each fog node. To tackle these challenges, this paper presents an Adaptive Load-Balancing Multi-Criteria Scheduling Algorithm (ALB-MCSA). The algorithm is designed to incorporate the load balancing algorithm alongside multi-criteria optimization in order to minimize the completion time, energy consumption, and operational cost. The algorithm ensures optimal resource utilization and increased performance by adjusting the weights and evenly distributing the load among the processors. Simulation results depict improved performance in terms of completion time, energy efficiency, operational cost and load distribution. Furthermore, a comparative analysis with conventional algorithms such as FCFS, PRIORITY, and EDF demonstrates the superior performance of the proposed approach across key evaluation metrics.