Performance Optimization by Task Scheduling in Cloud Computing
Amit Kaushal1, Sarvpal Singh2
1Amit Kaushal, Department of Computer Science & Engineering, MMMUT, Gorakhpur (U.P), India.
2Sarvpal Singh, Professor & Head, Department of ITCA, MMMUT, Gorakhpur (U.P), India.
Manuscript received on 24 November 2019 | Revised Manuscript received on 07 December 2019 | Manuscript Published on 14 December 2019 | PP: 20-24 | Volume-9 Issue-1S October 2019 | Retrieval Number: A10041091S19/19©BEIESP | DOI: 10.35940/ijeat.A1004.1091S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cloud computing is associate on demand access to a shared pool of resources. Vendor’s of cloud computing offer application and change technology, infrastructure, hardware, software, and integration for consumer. The most aspect of cloud computing is accessibility and performance of their network association. It refers to the method of allocating users’ tasks to virtual machines (VMs) with a goal of minimizing the work time and rising the resource utilization. Tasks programming is taken into account NP onerous drawback with O (m, n) run time complexness to schedule n tasks on m resources. A computer hardware adapts its programming strategy consistent with the ever-changing setting and therefore the variety of task. We provide comparison with Max–min scheduling formula and Genetic formula. Our hybrid algorithm provides higher performance compared to different programming algorithm.
Keywords: Task Scheduling, Cloud Computing, Auction Based Task Scheduling Algorithm, Genetic Algorithm, Max–Min Scheduling Algorithm.
Scope of the Article: Cloud Computing