Budget Constrained Execution of Multiple Bag-of-Tasks Applications on the Cloud

TL;DR

This paper presents a heuristic scheduling algorithm for multiple Bag-of-Tasks applications on the cloud that maximizes performance within a fixed budget, outperforming existing methods especially under tight budget constraints.

Contribution

The paper introduces a novel heuristic algorithm that schedules multiple BoT applications without resource limits, achieving better performance and consistency compared to existing approaches.

Findings

Achieves an average of 10% performance improvement over existing methods.

Maintains consistent performance even with low budget constraints.

No limits on cloud resources are required in the proposed scheduling algorithm.

Abstract

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.