Add to ORKGAbstract: We consider continuous-time Markov chains representing queueing systems in random environment and we obtain necessary and sufficient conditions for having product-form stationary distributions. The related topics of partial balance and the ESTA property are also studied. As an illustration, we apply the results to study the stationary distributions of Jackson networks in random environment. For models that do not satisfy the product-form conditions, we develop a product-form approximation, which is proved to be very good for models evolving in a slowly changing random environment. We justify this fact and we propose a methodology for estimating the error of this approximation
In this paper we present a class of queueing models with multiple job types, multiple machines and ...
We consider a single server system with infinite waiting room in a random environment. The service s...
International audienceWe consider Stochastic Automata Networks (SANs) in continuous time and we prov...
Product-forms are well-known in the community of performance evaluation because they allow the compu...
International audienceWe consider Stochastic Automata Networks (SAN) in continuous time and we prove...
Product-form models are a class of Markovian models whose steady-state solution can be computed effi...
In this paper we address the problem of efficiently deriving the steady-state distribution for a con...
We consider Stochastic Automata Networks (SAN) in con-tinuous time and we prove a sufficient conditi...
A resurgence in product-forms Interest in the stochastic behaviour of queueing networks began in the...
Exact results for product-form stationary distributions of Markov chains are of interest in differen...
In the last few years some novel approaches have been developed to analyse Markovian stochastic mode...
A class of queueing networks has a product-form solution. It is interesting to investigate which que...
In this article some new product theorems for opened and closed queuing networks with finite number ...
We consider a continuous time Markov process (X, L), where X jumps between a finite number of states...
In the paper, we study general Markovian models of loss systems with random resource requirements, i...
In this paper we present a class of queueing models with multiple job types, multiple machines and ...
We consider a single server system with infinite waiting room in a random environment. The service s...
International audienceWe consider Stochastic Automata Networks (SANs) in continuous time and we prov...
Product-forms are well-known in the community of performance evaluation because they allow the compu...
International audienceWe consider Stochastic Automata Networks (SAN) in continuous time and we prove...
Product-form models are a class of Markovian models whose steady-state solution can be computed effi...
In this paper we address the problem of efficiently deriving the steady-state distribution for a con...
We consider Stochastic Automata Networks (SAN) in con-tinuous time and we prove a sufficient conditi...
A resurgence in product-forms Interest in the stochastic behaviour of queueing networks began in the...
Exact results for product-form stationary distributions of Markov chains are of interest in differen...
In the last few years some novel approaches have been developed to analyse Markovian stochastic mode...
A class of queueing networks has a product-form solution. It is interesting to investigate which que...
In this article some new product theorems for opened and closed queuing networks with finite number ...
We consider a continuous time Markov process (X, L), where X jumps between a finite number of states...
In the paper, we study general Markovian models of loss systems with random resource requirements, i...
In this paper we present a class of queueing models with multiple job types, multiple machines and ...
We consider a single server system with infinite waiting room in a random environment. The service s...
International audienceWe consider Stochastic Automata Networks (SANs) in continuous time and we prov...