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An Improved Task Scheduling Mechanism Using Multi-Criteria Decision Making in Cloud Computing

An Improved Task Scheduling Mechanism Using Multi-Criteria Decision Making in Cloud Computing

Suvendu Chandan Nayak, Chitaranjan Tripathy
Copyright: © 2019 |Volume: 14 |Issue: 2 |Pages: 26
ISSN: 1554-1045|EISSN: 1554-1053|EISBN13: 9781522564492|DOI: 10.4018/IJITWE.2019040106
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MLA

Nayak, Suvendu Chandan, and Chitaranjan Tripathy. "An Improved Task Scheduling Mechanism Using Multi-Criteria Decision Making in Cloud Computing." IJITWE vol.14, no.2 2019: pp.92-117. http://doi.org/10.4018/IJITWE.2019040106

APA

Nayak, S. C. & Tripathy, C. (2019). An Improved Task Scheduling Mechanism Using Multi-Criteria Decision Making in Cloud Computing. International Journal of Information Technology and Web Engineering (IJITWE), 14(2), 92-117. http://doi.org/10.4018/IJITWE.2019040106

Chicago

Nayak, Suvendu Chandan, and Chitaranjan Tripathy. "An Improved Task Scheduling Mechanism Using Multi-Criteria Decision Making in Cloud Computing," International Journal of Information Technology and Web Engineering (IJITWE) 14, no.2: 92-117. http://doi.org/10.4018/IJITWE.2019040106

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Abstract

In this work, the authors propose Multi-criteria Decision-making to schedule deadline based tasks in cloud computing. The existing backfilling task scheduling algorithm could not handle similar tasks for scheduling. In backfilling algorithm, tasks are backfilled to provide ideal resources to schedule other deadline sensitive tasks. However, the task to be backfilled is selected on first come, first serve (FCFS) basis from scheduling queue. The scheduling performances require to be improved when, there are similar tasks. In this proposed work, the authors propose to implement MCDM technique, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) to improve the performance of the backfilling algorithm through scheduling deadline sensitive tasks in cloud computing. It resolves the conflicts among the similar tasks that is used as a decision support system. The work is simulated with synthetic data sets based on slack values of the tasks. The performance results affirm the task completion and reduction in task rejection compared to the existing backfilling algorithm.

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