Tasks Scheduling with Virtual Machines of the Deadline-Aware Priority Scheduling Model in Cloud Computing

Authors

  • Arvind Kumar Singh Research Scholar, Dept. of Computer Science, Maharishi University of Information Technology, Lucknow
  • Hitendra Singh Assistant Professor, School of Engineering and Technology, Maharishi University of Information Technology, Lucknow
  • Manish Varsney Professor, School of Engineering & Technology, Maharishi University of Information Technology, Lucknow

Keywords:

Task scheduling, Cloud Computing, Load, balancing, Priority Scheduling model

Abstract

Cloud computing involves providing applications as services over the Internet, encompassing both the software applications provided as Software as a Service (SaaS) and the hardware and systems software housed in datacenters supporting these services. An Open Cloud, offering utility computing services, is characterized by its availability to the public on a pay-as-you-go model. The Cloud Sim toolkit serves as a tool for configuring and optimizing policies across all Cloud Sim components, making it a valuable resource for studying the complexities arising from diverse scenarios. For simulation tests, a laptop with the following specifications will be employed: a 2.5 GHz Intel Core i5 processor, 4 GB of RAM, and a 512 GB hard drive. The DAPS model adopts a methodology where tasks are prioritized in ascending order based on length, and the state of the Virtual Machine (VM) is deemed successful if it meets the deadline constraint. Subsequently, various jobs are allocated to the appropriate VM’s, aiming to minimize the makespan and completion time. Experimental results indicate that the proposed approach outperforms existing techniques by reducing average makespan while enhancing the diversity of tasks

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Published

13.12.2023

How to Cite

Singh, A. K. ., Singh, H. ., & Varsney, M. . (2023). Tasks Scheduling with Virtual Machines of the Deadline-Aware Priority Scheduling Model in Cloud Computing. International Journal of Intelligent Systems and Applications in Engineering, 12(8s), 123–127. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4101

Issue

Vol. 12 No. 8s (2024)

Section

Research Article

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