The Experiential Heterogeneous Earliest Finish Time Algorithm for Task Scheduling in Clouds

Artan Mazrekaj, Arlinda Sheholli, Dorian Minarolli, Bernd Freisleben

Abstract

Task scheduling in cloud environments is the problem of assigning and executing computational tasks on the available cloud resources. Effective task scheduling approaches reduce the task completion time, increase the efficiency of resource utilization, and improve the quality of service and the overall performance of the system. In this paper, we present a novel task scheduling algorithm for cloud environments based on the Heterogeneous Earliest Finish Time (HEFT) algorithm, called experiential HEFT. It considers experiences with previous executions of tasks to determine the workload of resources. To realize the experiential HEFT algorithm, we propose a novel way of HEFT rank calculation to specify the minimum average execution time of previous runs of a task on all relevant resources. Experimental results indicate that the proposed experiential HEFT algorithm performs better than HEFT and the popular Critical-Path-on-a-Processor (CPOP) algorithm considered in our comparison.

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Paper Citation


in Harvard Style

Mazrekaj A., Sheholli A., Minarolli D. and Freisleben B. (2019). The Experiential Heterogeneous Earliest Finish Time Algorithm for Task Scheduling in Clouds.In Proceedings of the 9th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-365-0, pages 371-379. DOI: 10.5220/0007722203710379


in Bibtex Style

@conference{closer19,
author={Artan Mazrekaj and Arlinda Sheholli and Dorian Minarolli and Bernd Freisleben},
title={The Experiential Heterogeneous Earliest Finish Time Algorithm for Task Scheduling in Clouds},
booktitle={Proceedings of the 9th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2019},
pages={371-379},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007722203710379},
isbn={978-989-758-365-0},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - The Experiential Heterogeneous Earliest Finish Time Algorithm for Task Scheduling in Clouds
SN - 978-989-758-365-0
AU - Mazrekaj A.
AU - Sheholli A.
AU - Minarolli D.
AU - Freisleben B.
PY - 2019
SP - 371
EP - 379
DO - 10.5220/0007722203710379