Multi-objective workflow scheduling scheme: a multi-criteria decision making approach

Scheduling large workflows that are faced in many business as well as scientific domains such as economy, bioinformatics, astronomy and geophysics is an important area of research in the field of cloud computing. Many studies have been made to develop efficient algorithms for workflow scheduling tha...

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Bibliographic Details
Published in:Journal of ambient intelligence and humanized computing Vol. 12; no. 12; pp. 10789 - 10808
Main Authors: Kumar, Madhu Sudan, Tomar, Abhinav, Jana, Prasanta K.
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2021
Springer Nature B.V
Subjects:
Algorithms
Artificial Intelligence
Astronomy
Bioinformatics
Cloud computing
Computational Intelligence
Decision making
Energy consumption
Energy efficiency
Engineering
Entropy
Entropy (statistics)
Geophysics
Multiple criteria decision making
Multiple criterion
Multiple objective analysis
Optimization
Original Research
Risk management
Robotics and Automation
Scheduling
User Interfaces and Human Computer Interaction
Weighting methods
Workflow
Cloud computing
EWM
MCDM
Workflow scheduling
TOPSIS
ISSN:1868-5137, 1868-5145
Online Access:Get full text
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Summary:Scheduling large workflows that are faced in many business as well as scientific domains such as economy, bioinformatics, astronomy and geophysics is an important area of research in the field of cloud computing. Many studies have been made to develop efficient algorithms for workflow scheduling that deal with multiple objectives. In the recent years, multi-criteria decision making (MCDM) methods have become popular for solving such multi-objective problems in various areas like risk management, climate change, renewable energy and so on. Particularly, the MCDM method called technique for order of preference by similarity to ideal solution (TOPSIS) has drawn extensive attention due to its easy understanding, fast and simple calculation. In this paper, we present a workflow scheduling algorithm in cloud environment based on TOPSIS that integrates entropy weight method (EWM). The proposed algorithm aims at minimizing makespan, cost, and energy consumption and maximizing the reliability. The algorithm is tested on various benchmark scientific workflows. The simulation results are compared with that of the related algorithms. The comparisons show that the proposed algorithm performs remarkably well in terms of cost and energy consumption while maintaining the other parameters within considerable limits.
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ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-020-02833-y