Optimal server resource reservation policies for priority classes of users under cyclic non-homogeneous markov modeling
Resource availability optimization is studied on a server–client system where different users are partitioned into priority classes. The aim is to provide higher resource availability according to the priority of each class. For this purpose, resource reservation is modeled by a homogeneous continuo...
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| Veröffentlicht in: | European journal of operational research Jg. 198; H. 2; S. 545 - 556 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Amsterdam
Elsevier B.V
16.10.2009
Elsevier Elsevier Sequoia S.A |
| Schriftenreihe: | European Journal of Operational Research |
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| ISSN: | 0377-2217, 1872-6860 |
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| Abstract | Resource availability optimization is studied on a server–client system where different users are partitioned into priority classes. The aim is to provide higher resource availability according to the priority of each class. For this purpose, resource reservation is modeled by a homogeneous continuous time Markov chain (CTMC), but also by a cyclic non-homogeneous Markov chain (CNHMC) as there is a cyclic behavior of the users’ requests for resources. The contribution of the work presented consists in the formulation of a multiobjective optimization problem for both the above cases that aims to determine the optimal resource reservation policy providing higher levels of resource availability for all classes. The optimization problem is solved either with known methods or with a proposed kind of heuristic algorithm. Finally, explicit generalized approximate inverse preconditioning methods are adopted for solving efficiently sparse linear systems that are derived, in order to compute resource availability. |
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| AbstractList | Resource availability optimization is studied on a server-client system where different users are partitioned into priority classes. The aim is to provide higher resource availability according to the priority of each class. For this purpose, resource reservation is modeled by a homogeneous continuous time Markov chain (CTMC), but also by a cyclic non-homogeneous Markov chain (CNHMC) as there is a cyclic behavior of the users' requests for resources. The contribution of the work presented consists in the formulation of a multiobjective optimization problem for both the above cases that aims to determine the optimal resource reservation policy providing higher levels of resource availability for all classes. The optimization problem is solved either with known methods or with a proposed kind of heuristic algorithm. Finally, explicit generalized approximate inverse preconditioning methods are adopted for solving efficiently sparse linear systems that are derived, in order to compute resource availability. Resource availability optimization is studied on a server-client system where different users are partitioned into priority classes. The aim is to provide higher resource availability according to the priority of each class. For this purpose, resource reservation is modeled by a homogeneous continuous time Markov chain (CTMC), but also by a cyclic non-homogeneous Markov chain (CNHMC) as there is a cyclic behavior of the users' requests for resources. The contribution of the work presented consists in the formulation of a multiobjective optimization problem for both the above cases that aims to determine the optimal resource reservation policy providing higher levels of resource availability for all classes. The optimization problem is solved either with known methods or with a proposed kind of heuristic algorithm. Finally, explicit generalized approximate inverse preconditioning methods are adopted for solving efficiently sparse linear systems that are derived, in order to compute resource availability. [PUBLICATION ABSTRACT] |
| Author | Gravvanis, G.A. Koutras, V.P. Platis, A.N. |
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| Cites_doi | 10.1016/j.amc.2007.01.024 10.1109/12.2184 10.1007/BFb0013869 10.1007/978-3-540-30208-7_74 10.1023/B:JMMA.0000015836.94997.2c 10.1016/S0377-2217(01)00190-4 10.1007/BF03041466 10.1016/S0305-0548(02)00069-2 10.1109/PRDC.2006.54 10.1007/s11227-007-0129-1 10.1109/4234.1001668 10.1016/j.camwa.2005.11.009 10.1016/S0377-2217(99)00183-6 10.1057/palgrave.jors.2602100 10.1016/S0305-0548(99)00121-5 10.1109/TAC.2002.1008369 10.1016/j.cor.2007.02.009 10.1109/25.933303 10.1016/S0951-8320(97)00073-2 10.1109/MMCS.1998.693623 10.1109/24.556582 10.1016/j.ejor.2004.08.008 10.1023/A:1020538522302 10.1109/LCOMM.2002.802048 |
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| Keywords | Server resources Approximate inverse matrix algorithms Resource availability modeling Non-homogeneous Markov chains Priority classes Preconditioning Optimization Markov process Homogeneous model Resource allocation Optimal policy Multiobjective programming Continuous time Generalized inverse Modeling Markov chain Inverse matrix Sparse matrix Service differentiation Mathematical programming Availability Priority Client server architecture Inverse problem Heuristic method User behavior |
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| SubjectTerms | Applied sciences Approximate inverse matrix algorithms Approximation Decision theory. Utility theory Exact sciences and technology Heuristic Markov analysis Non-homogeneous Markov chains Operational research and scientific management Operational research. Management science Optimization Optimization algorithms Preconditioning Priority classes Resource allocation Resource availability modeling Server resources Server resources Priority classes Resource availability modeling Non-homogeneous Markov chains Optimization Approximate inverse matrix algorithms Preconditioning Stochastic models Studies |
| Title | Optimal server resource reservation policies for priority classes of users under cyclic non-homogeneous markov modeling |
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