RETRACTED ARTICLE: An efficient cost-based algorithm for scheduling workflow tasks in cloud computing systems

• Published in: Neural computing & applications Vol. 31; no. 5; pp. 1353 - 1363
• Main Authors: Amoon, Mohammed, El-Bahnasawy, Nirmeen, ElKazaz, Mai
• Format: Journal Article
• Language: English
• Published: London Springer London 03.05.2019; Springer Nature B.V
• Subjects: Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Image Processing and Computer Vision; Probability and Statistics in Computer Science; S.I. : Emerging Intelligent Algorithms for Edge-of-Things Computing; Task scheduling; Cloud computing; Directed acyclic graph; Schedule length; Monetary cost
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-018-3610-2

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.