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Authors: Artan Mazrekaj 1 ; Arlinda Sheholli 2 ; Dorian Minarolli 3 and Bernd Freisleben 4

Affiliations: 1 Faculty of Contemporay Sciences and Technologies, SEEU University, Tetovo and Republic of North Macedonia ; 2 Faculty of Electrical and Computer Engineering, University of Prishtina, Prishtina and Kosovo ; 3 Faculty of Information Technology, Polytechnic University of Tirana, Tirana and Albania ; 4 Department of Mathematics and Computer Science, University of Marburg, Marburg and Germany

Keyword(s): Cloud Computing, Task Scheduling, Resource Allocation.

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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
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 - CLOSER; ISBN 978-989-758-365-0; ISSN 2184-5042, SciTePress, pages 371-379. DOI: 10.5220/0007722203710379

@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 - CLOSER},
year={2019},
pages={371-379},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007722203710379},
isbn={978-989-758-365-0},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Cloud Computing and Services Science - CLOSER
TI - The Experiential Heterogeneous Earliest Finish Time Algorithm for Task Scheduling in Clouds
SN - 978-989-758-365-0
IS - 2184-5042
AU - Mazrekaj, A.
AU - Sheholli, A.
AU - Minarolli, D.
AU - Freisleben, B.
PY - 2019
SP - 371
EP - 379
DO - 10.5220/0007722203710379
PB - SciTePress

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