Multi-QoS constrained and Profit-aware scheduling approach for concurrent workflows on heterogeneous systems

Abstract

The execution of a workflow application can result in an imbalanced workload among allocatedprocessors, ultimately resulting in a waste of resources and a higher cost to the user. Here, we considera dynamic resource management system in which processors are reserved not for a job but only to run atask, thus allowing a higher resource usage rate. This paper presents a scheduling algorithm that managesconcurrent workflows in a dynamic environment in which jobs are submitted by users at any moment intime, on shared heterogeneous resources, and constrained to a specified budget and deadline for each job.Recent research attempted to propose dynamic strategies for concurrent workflows but only addressedfairness in resource sharing among applications while minimizing the execution time. The Multi-QoSProfit-Aware scheduling algorithm (MQ-PAS) proposed here is able to increase the profit achieved by theprovider by considering the budget available for each job to define tasks priorities. We study the scalabilityof the algorithm with different types of workflows and infrastructures. The experimental results showthat our strategy improves provider revenue significantly and obtains comparable successful rates ofcompleted jobs.