Budget constrained execution of multiple Bag-of-Tasks applications on the Cloud

This research is supported by the EPSRC grant ‘Working Together: Constraint Programming and Cloud Computing’ (EP/K015745/1), a Royal Society Industry Fellowship ‘Bringing Science to the Cloud’, an EPSRC Impact Acceleration Grant (IAA) and an Amazon Web Services (AWS) Education Research Grant.Optimising the execution of Bag-of-Tasks (BoT) applications on the cloud is a hard problem due to the trade- offs between performance and monetary cost. The problem can be further complicated when multiple BoT applications need to be executed. In this paper, we propose and implement a heuristic algorithm that schedules tasks of multiple applications onto different cloud virtual machines in order to maximise performance while satisfying a given budget constraint. Current approaches are limited in task scheduling since they place a limit on the number of cloud resources that can be employed by the applications. However, in the proposed algorithm there are no such limits, and in comparison with other approaches, the algorithm on average achieves an improved performance of 10%. The experimental results also highlight that the algorithm yields consistent performance even with low budget constraints which cannot be achieved by competing approaches.Postprin