The AMVA priority approximation |
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| Affiliation: | 1. Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN 37831, USA;2. Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA;1. The Management School of Xi’an Jiaotong University, The State Key Lab for Manufacturing Systems Engineering, The Key Lab of Ministry of Education for Process Control & Efficiency Engineering, Xi’an 710049, China;2. Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region;3. Automated Scheduling Optimization and Planning (ASAP) Group, School of Computer Science and Information Technology, Jubilee Campus, University of Nottingham, Nottingham NG8 1BB, UK;4. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region;1. Louvain School of Management – Center for Operations Research and Econometrics, Place des Doyens 1, Université catholique de Louvain, 1348 Louvain-la-Neuve, Belgium;2. Logistics Research Centre, School of Management and Languages, Heriot-Watt University, Edinburgh EH14 4AS, UK;1. School of Environment and Energy, South China University of Technology, Guangzhou 510006, China;2. School of Environmental Science and Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China;3. The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, Guangzhou 510006, China |
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| Abstract: | Most computer systems contain one or more system resources whose usage is controlled on the basis of workload priorities. Unfortunately, the exact analysis of queueing network models incorporating priority scheduling disciplines is usually infeasible. The MVA Priority Approximation has been proposed as a comparatively inexpensive, and yet reasonably accurate, approximation technique for queueing networks with priority scheduled service centers. Even this algorithm, however, is too expensive to apply to large networks with many classes of customers.In this paper, we show how the MVA Priority Approximation can be modified so that it utilizes approximate rather than exact Mean Value Analysis (MVA), without significant loss of accuracy. Extensive numerical experiments are performed to further assess the accuracy of the modified algorithm, termed here the AMVA Priority Approximation. These experiments utilize the parameter space mapping technique for studying ‘local’ queueing network approximations. |
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