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Queueing Systems with Resume Level
Ukrainian Mathematical Journal, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bratiichuk, M. S., Sliwinska, D.
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International Journal of Applied and Computational Mathematics, 2020
R. Sethi, Madhu Jain, R. Meena, D. Garg
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R. Sethi, Madhu Jain, R. Meena, D. Garg
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1997
In this chapter we consider the two single server queuing systems: (i)M/E k /1 with Poisson arrivals and Erlangian service time density, and (ii)E k /M/1 with Erlangian arrivals and exponential service time density. In both systems the processes of interest are the queue length Q(t) and the waiting time W(t).
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In this chapter we consider the two single server queuing systems: (i)M/E k /1 with Poisson arrivals and Erlangian service time density, and (ii)E k /M/1 with Erlangian arrivals and exponential service time density. In both systems the processes of interest are the queue length Q(t) and the waiting time W(t).
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Mathematica Applicanda, 1982
From the introduction: "We represent network systems with a Poisson arrival stream whose parameter depends on the actual state of the system. We define a process which describes the operation of a system and present an ergodic theorem (the construction of the process and the concept of the theorem are based on a paper by I. N. Kovalenko [Izv.
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From the introduction: "We represent network systems with a Poisson arrival stream whose parameter depends on the actual state of the system. We define a process which describes the operation of a system and present an ergodic theorem (the construction of the process and the concept of the theorem are based on a paper by I. N. Kovalenko [Izv.
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Queueing Systems with Opposite Queues
2022Anastasija Glushakova, Alexander Kovshov
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1997
We begin our study of queueing systems by considering some simple models in which customers arrive in a Poisson process at a rate λ(0 < λ < ∞) and are served by s customers (1 ≤ s < ∞) in parallel on a first come, first served basis, the service times of customers having the exponential density μe -μx (0 < x < ∞).
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We begin our study of queueing systems by considering some simple models in which customers arrive in a Poisson process at a rate λ(0 < λ < ∞) and are served by s customers (1 ≤ s < ∞) in parallel on a first come, first served basis, the service times of customers having the exponential density μe -μx (0 < x < ∞).
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2012
Traditional telephone networks were designed to implement a single type of communication service, i.e., the telephone service. Today’s telecommunication networks implement a wide range of communication services. In this section we introduce Markov models of communication services that compete for the bandwidth of a finite-capacity communication link.
László Lakatos +2 more
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Traditional telephone networks were designed to implement a single type of communication service, i.e., the telephone service. Today’s telecommunication networks implement a wide range of communication services. In this section we introduce Markov models of communication services that compete for the bandwidth of a finite-capacity communication link.
László Lakatos +2 more
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2015
Most realistics computer and communication systems are very complex networks of subsytems and the jobs processed by such systems involve wide-ranging service requirements. In many cases the arrival and service processes are non-Markovian and the service discipline may use priorities in scheduling service requests. While Mean Value Ananlysis can be used
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Most realistics computer and communication systems are very complex networks of subsytems and the jobs processed by such systems involve wide-ranging service requirements. In many cases the arrival and service processes are non-Markovian and the service discipline may use priorities in scheduling service requests. While Mean Value Ananlysis can be used
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1999
This chapter describes a spatial queueing model for stochastic service systems in which customers or units move about and receive services in a region or a general space. The state of such a system is a point process on a space that evolves over time as a “measure-valued” Markov jump process.
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This chapter describes a spatial queueing model for stochastic service systems in which customers or units move about and receive services in a region or a general space. The state of such a system is a point process on a space that evolves over time as a “measure-valued” Markov jump process.
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Methods for Analysis of Multi-Channel Queueing System with Instantaneous and Delayed Feedbacks
Cybernetics and Systems Analysis, 2016V. S. Koroliuk +3 more
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