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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Bibliographic Details
Published in:European journal of operational research Vol. 198; no. 2; pp. 545 - 556
Main Authors: Koutras, V.P., Platis, A.N., Gravvanis, G.A.
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 16.10.2009
Elsevier
Elsevier Sequoia S.A
Series:European Journal of Operational Research
Subjects:
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
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
ISSN:0377-2217, 1872-6860
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Summary: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.
Bibliography:SourceType-Scholarly Journals-1
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content type line 14
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2008.09.031