Abstract
Task scheduling is critical in fog computing, as it has to assign workloads to fog nodes to save costs and execution times. This study emphasizes the allocation of jobs received from clients to suitable nodes through a proposed scheduling technique, which is deployed on layer 2 servers within a cloud-fog environment. Laxity-based Cost-efficient Task Scheduling (LCTS) is proposed for contemporary task scheduling difficulties, such as balancing cost and delay with optimal energy utilization. The results show that the proposed strategy decreased execution time and cost more than Round Robin (RR) and Genetic Algorithm (GA). Furthermore, the proposed method was less expensive than cloud-based IoT solutions. Compared to GA and RR, the simulation results showed that cost and execution time were reduced by 6.99%-17.36% and 4.58%-9.09%, respectively.
Published Version
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