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dc.contributor.authorCastel-Taleb, Hind
dc.contributor.authorMokdad, Lynda
dc.date.accessioned2010-12-07T10:01:43Z
dc.date.available2010-12-07T10:01:43Z
dc.date.issued2005
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/5249
dc.language.isoenen
dc.subjectMobile Networksen
dc.subjectQuality of Serviceen
dc.subjectStochastic orderingen
dc.subjectstochastic comparisonsen
dc.subjectContinuous Time Markov Chainsen
dc.subject.ddc004en
dc.titlePerformance measure bounds in mobile networks by state space reductionen
dc.typeCommunication / Conférence
dc.description.abstractenWe present in this paper a mathematical method based on stochastic comparisons of Markov chains in order to compute in a mobile network performance measures that are important QoS parameters for users: the dropping handover of voice and the blocking probability of a new voice call. The key idea of this methodology is that given a complex system represented by a multi-dimensional Markov chain which is too large to be solved, we propose to reduce the state space, and so to define a new Markov chain which is a simplified version of the original one. This reduced Markov chain is defined as an aggregated one, which represents a stochastic bound for performance measures written as increasing reward function on the stationary distribution. The main steps of the construction of the aggregated Markov chain applied into mobile networks are presented in this paper. As the number of mobile users with different kinds of applications increases, the associated model is more complex and it can be represented by multi-dimensional continuous time Markov chain with a very large size. Thus, we define an aggregated Markov chain represented by a multi-dimensional birth and death process which is very easy to solve. We have proved that there is a weak ordering between the original Markov chain and the aggregated one using increasing set formalism. We have computed upper bounds of dropping handover and blocking probability for different values of input parameters. Numerical results prove that upper bounds give good results and so the stochastic methodology is an interesting mathematical tool for the performance evaluation of complex systems.en
dc.identifier.citationpages1526-1539en
dc.relation.ispartoftitle13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, 2005en
dc.relation.ispartofpublnameIEEE Pressen
dc.relation.ispartofdate2005
dc.description.sponsorshipprivateouien
dc.subject.ddclabelInformatique généraleen
dc.relation.ispartofisbn0-7695-2458-3en
dc.relation.conftitle13th IEEE / ACM International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems (MASCOTS 2005)en
dc.relation.confdate2005-09
dc.relation.confcityAtlantaen
dc.relation.confcountryÉtats-Unisen
dc.identifier.doihttp://dx.doi.org/10.1109/MASCOTS.2005.52


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