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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This work was supported by King Saud University, Deanship of Scientific Research, Community College Research Unit.
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Amoon, M., El-Bahnasawy, N. & ElKazaz, M. An efficient cost-based algorithm for scheduling workflow tasks in cloud computing systems. Neural Comput & Applic 31, 1353–1363 (2019). https://doi.org/10.1007/s00521-018-3610-2
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DOI: https://doi.org/10.1007/s00521-018-3610-2