Indonesian Journal of Electrical Engineering and Computer Science
Vol 25, No 1: January 2022

Effective task scheduling algorithm in cloud computing with quality of service alert bees and grey wolf optimization

Nidhi Bansal (Formerly Uttar Pradesh Technical University)
Ajay Kumar Singh (Formerly Uttar Pradesh Technical University)



Article Info

Publish Date
01 Jan 2022

Abstract

Quality-based services are an indicative factor in providing a meaningful measure. These measures allow labeling for upcoming targets with a numerical comparison with a valid mathematical proof of reading and publications. By obtaining valid designs, organizations put this measure into the flow of technology development operations to generate higher profits. Since the conditions were met from the inception of cloud computing technology, the market was captured heavily by providing support through cloud computing. With the increase in the use of cloud computing, the complexity of data has also increased greatly. Applying natural theory to cloud technology makes it a fruit cream. Natural methods often come true, because survival depends on the live events and happenings, so using it in real life as well as any communication within technology will always be reliable. The numerical results are also showing a better value by comparing the optimization method. Finally, the paper introduces an adaptation theory with effective cloudsim coding of honey bees and grey wolf in conjunction with their natural life cycle for solving task scheduling problems. Using adapted bees improved the results by 50% compared with the original bees and secondly by honeybees and grey wolf improved 60%.

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