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Published in: Neural Computing and Applications 5/2019

02-07-2018 | S.I. : Emerging Intelligent Algorithms for Edge-of-Things Computing

An efficient cost-based algorithm for scheduling workflow tasks in cloud computing systems

Authors: Mohammed Amoon, Nirmeen El-Bahnasawy, Mai ElKazaz

Published in: Neural Computing and Applications | Issue 5/2019

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Abstract

Cloud computing has become a highly required platform in fields of information technology due to providing inexpensive services with high availability and scalability. The dynamic and diverse nature of the cloud computing systems makes scheduling of workflow tasks a pivotal issue. This paper proposes an algorithm to schedule applications’ tasks to virtual machines (VMs) of cloud computing systems. The algorithm has three phases: level sorting, task-prioritizing and virtual machine selection. The three-phase process successfully assigns the virtual machine for each task without making any difficulties for evaluating the algorithm performance; extensive simulation experiments are performed. The introduced ICTS algorithm analyzes each incoming task which is sorted and ranked while assigning the virtual machine to the particular task which improves the overall scheduling process because it processes the job according to the importance. Then the efficiency of the system is evaluated using experimental results that indicate the improved cost task scheduling (ICTS) algorithm provides an improvement in schedule length as well as significant monetary cost saving.

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Metadata
Title
An efficient cost-based algorithm for scheduling workflow tasks in cloud computing systems
Authors
Mohammed Amoon
Nirmeen El-Bahnasawy
Mai ElKazaz
Publication date
02-07-2018
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 5/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3610-2

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