Joint Customer/Provider Evolutionary Multi-objective Utility Maximization in Cloud Data Center Networks
| Autor: | Mehdi Hosseinpour, Muhammad R. Ahmadi, Pejman Goudarzi |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Multi-core processor
Optimization problem Computer Networks and Communications business.industry Computer science Distributed computing Energy Engineering and Power Technology Cloud computing 02 engineering and technology computer.software_genre Set (abstract data type) Constraint (information theory) Virtual machine 020204 information systems Signal Processing 0202 electrical engineering electronic engineering information engineering Feature (machine learning) Resource allocation 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Electrical and Electronic Engineering business computer |
| Zdroj: | Iranian Journal of Science and Technology, Transactions of Electrical Engineering. 45:479-492 |
| ISSN: | 2364-1827 2228-6179 |
| DOI: | 10.1007/s40998-020-00381-x |
| Popis: | Cloud computing has found an important role in cost-effective and elastic network resource allocation community. Most researchers and practitioners have focused on cloud provider side for efficient resource allocation to end-users and to warrant their service-level agreements (SLAs). Due to heterogeneous user demands which request services from cloud data center networks, simultaneous satisfaction of all users to their pre-defined SLA level while making the cloud provider and all of the data centers to be cost-effective in terms of the financial income and energy-efficiency is a challenging issue. To address this problem, in the current work, the efficient joint provider/customer efficient resource allocation has been first formulated as a multi-objective optimization problem with convex constraint set in terms of virtual machine (VM) parameters (e.g., storage, CPU core, memory, etc.). Then, an evolutionary solution based on cooperative co-evolution algorithm has been proposed that can conduct a divide-and-conquer methodology for solving the complex optimization problem. Numerical results show the prominent feature of the method in terms of VM usage effectiveness and overall joint network cost/user SLA satisfaction. |
| Databáze: | OpenAIRE |
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