IJBTT

CS Optimized Task Scheduling for Cloud Data Management

CS Optimized Task Scheduling for Cloud Data Management
	© 2022 by IJETT Journal
	Volume-70 Issue-6
	Year of Publication : 2022
	Authors : Mandeep Singh, Shashi Bhushan
	DOI : 10.14445/22315381/IJETT-V70I6P214

How to Cite?

Mandeep Singh, Shashi Bhushan, "CS Optimized Task Scheduling for Cloud Data Management," International Journal of Engineering Trends and Technology, vol. 70, no. 6, pp. 114-121, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I6P214

Abstract
Task scheduling is the most recent networking technology in cloud computing. Among various technologies, the concept of Virtualization, dynamic sharing, delivering quality service, and load balancing are some of the most attractive ones that require high attention. While scheduling tasks and sharing applications, the most important challenge is to minimize execution time while maintaining the quality of service in terms of Service Level Agreement (SLA) and energy consumption. In the present paper, the authors proposed a Cuckoo Search Optimization to improve the local search strategy and schedule tasks in the cloud computing environment. This iterative search mechanism integrated efficient task scheduling with the neural architecture to achieve secure scheduling. The simulation analysis performed up to 1000 tasks for 100 user requests in terms of SLA violation, and energy consumption demonstrated the effectiveness of the proposed CS optimized, secure scheduling.

Keywords
Cloud Computing, Cuckoo Search, Modified Best Fit Decreasing, Neural Network, Scheduling.

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