An optimization-based adaptive resource management framework for economic Grids: A switching mechanism |
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| Affiliation: | 1. Department of Computer Science & Engineering, Daffodil International University, Dhaka, Bangladesh;2. College of Engineering and Computer Science, Abu Dhabi University, United Arab Emirates;3. School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway, 46150, Selangor Darul Ehsan, Malaysia;1. Faculty of Science and Information Technology, Daffodil International University, Dhaka 1207, Bangladesh;2. Department of Mathematics and Statistics, College of Science, Sultan Qaboos University, P.O. Box 36, P.C. 123, Al-Khod, Muscat, Oman;1. Laboratory of Analytical Chemistry, Department of Chemistry, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece;2. Department of Chemistry and Biochemistry, Florida International University, Miami, FL, USA;3. Department of Pharmacy, Faculty of Allied Health Sciences, Daffodil International University, Dhaka 1207, Bangladesh;4. Laboratory of Pharmaceutical Analysis, Department of Pharmaceutical Technology, School of Pharmacy, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;1. Department of Electrical Engineering, Lorestan University, Khorramabad, Lorestan, Iran;2. Department of Electrical Engineering, Islamic Azad University–Khomeinishahr Branch, Khomeinishahr, Isfahan, Iran;1. Dept. of Electrical Engineering, Faculty of Engineering, Suez Canal University, 41522 Ismailia, Egypt;2. Faculty of Energy Systems and Nuclear Science, University of Ontario Institute of Technology, Oshawa, L1H7K4 ON, Canada;3. Sharaf Energy Inc., Fredericton, New Brunswick, Canada |
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| Abstract: | The application of Grid computing has been broadening day by day. An increasing number of users has led to the requirement of a job scheduling process, which can benefit them through optimizing their utility functions. On the other hand, resource providers are exploring strategies suitable for economically efficient resource allocation so that they can maximize their profit through satisfying more users. In such a scenario, economic-based resource management strategies (economic models) have been found to be compelling to satisfy both communities. However, existing research has identified that different economic models are suitable for different scenarios in Grid computing. The Grid application and resource models are typically very dynamic, making it challenging for a particular model for delivering stable performance all the time. In this work, our focus is to develop an adaptive resource management architecture capable of dealing with multiple models based on the models’ domains of strengths (DOS). Our preliminary results show promising outcomes if we consider multiple models rather than relying on a single model throughout the life cycle of a Grid. |
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| Keywords: | Grid computing Economic models Domains of strengths Switching Optimization |
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