Publication | Closed Access
Fairness Resource Sharing for Dynamic Workflow Scheduling on Heterogeneous Systems
69
Citations
8
References
2012
Year
Unknown Venue
Cluster ComputingConcurrent Workflow SchedulingEngineeringComputer ArchitectureSoftware EngineeringDynamic ApplicationSystems EngineeringParallel ComputingJob SchedulerCloud SchedulingComputer EngineeringFair Resource AllocationScheduling (Computing)Workflow Management SystemComputer ScienceWorkflow ExecutionFairness Resource SharingEdge ComputingCloud ComputingReal-time SystemsDynamic Application SchedulingScheduling (Project Management)System Software
For most Heterogeneous Computing Systems (HCS) the completion time of an application is the most important requirement. Many applications are represented by a workflow that is therefore schedule in a HCS system. Recently, researchers have proposed algorithms for concurrent workflow scheduling in order to improve the execution time of several applications in a HCS system. Although, most of these algorithms were designed for static scheduling, that is all application must be submitted at the same time, there are a few algorithms, such as OWM (online workflow Management) and RANK_HYBD, that were presented for dealing with dynamic application scheduling. In this paper, we present a new algorithm for dynamic application scheduling. The algorithm focus on the Quality of Service (QoS) experienced by each application (or user). It reduces the waiting and execution times of each individual workflow, unlike other algorithms that give privilege to average completion time of all workflows. The simulation results show that the proposed approach significantly outperforms the other algorithms in terms of individual response time.
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