Scheduling a Time-Varying Workload of Multiple Types of Jobs on Distributed Resources

Recent technological advances, such as cloud and fog computing, have made prevalent the utilization of distributed computational resources. There is a variety of complex workloads that need to be processed on such platforms. The type of the workload may vary over time. Two of the most important challenges in a distributed environment are efficient resource allocation and the employment of appropriate workload scheduling techniques. In this paper, we examine dynamic scheduling of complex workloads on distributed resources. The workload consists of single-task jobs, bag-of-task jobs and linear workflows. The characteristics of the investigated workload vary over time. Two scheduling techniques are studied. Simulation modeling is used to compare their performance under different workload and system load scenarios.