Vacation Models in Discrete Time
Queueing Systems: Theory and Applications
QoS and Energy Trade Off in Distributed Energy-Limited Mesh/Relay Networks: A Queuing Analysis
IEEE Transactions on Parallel and Distributed Systems
IEEE Transactions on Mobile Computing
Discrete-time GI/Geo/1 queue with multiple working vacations
Queueing Systems: Theory and Applications
Discrete-time GeoX/G/1 queue with unreliable server and multiple adaptive delayed vacations
Journal of Computational and Applied Mathematics
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ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Analysis of discrete-time batch service renewal input queue with multiple working vacations
Computers and Industrial Engineering
A discrete time inventory system with postponed demands
Journal of Computational and Applied Mathematics
Discrete-time GeoX/G(a,b)/1/N queues with single and multiple vacations
Mathematical and Computer Modelling: An International Journal
Computers and Industrial Engineering
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A class of single server vacation queues which have single arrivals and non-batch service is considered in discrete time. It is shown that provided the interarrival, service, vacation, and server operational times can be cast with Markov-based representation then this class of vacation model can be studied as a matrix–geometric or a matrix-product problem – both in the matrix–analytic family – thereby allowing us to use well established results from Neuts (1981). Most importantly it is shown that using discrete time approach to study some vacation models is more appropriate and makes the models much more algorithmically tractable. An example is a vacation model in which the server visits the queue for a limited duration. The paper focuses mainly on single arrival and single unit service systems which result in quasi-birth-and-death processes. The results presented in this paper are applicable to all this class of vacation queues provided the interarrival, service, vacation, and operational times can be represented by a finite state Markov chain.