On queueing with customer impatience until the beginning of service

Movaghar, Ali

doi:10.1109/ipds.1996.540216

Cited by 33 publications

(45 citation statements)

References 10 publications

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“…[1,2,3,4,5]). Several papers investigate the scheduling of different classes of jobs in a system with abandonment in order to minimize the (weighted) number of late jobs.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal static priority rules for stochastic scheduling with impatience

Salch

Gayon

Lemaire

2013

Operations Research Letters

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We consider a stochastic scheduling problem with impatience to the end of service or impatience to the beginning of service. The impatience of a job can be seen as a stochastic due date. Processing times and due dates are random variables. Jobs are processed on a single machine with the objective to minimize the expected weighted number of tardy jobs in the class of static list scheduling policies. We derive optimal schedules when processing times and due dates follow different probability distributions.

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“…[1,2,3,4,5]). Several papers investigate the scheduling of different classes of jobs in a system with abandonment in order to minimize the (weighted) number of late jobs.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal static priority rules for stochastic scheduling with impatience

Salch

Gayon

Lemaire

2013

Operations Research Letters

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“…They considered the more general M (n)/M (n)/c + G queue where arrival and service rates are allowed to depend on the number n of calls in the system. For the M (n)/M/c+ G queue, see Movaghar [16].…”

Section: Introductionmentioning

confidence: 99%

M/Ph/1 Queue With Deterministic Impatience Time

Kim¹,

Kim²

2013

Communications of the Korean Mathematical Society

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Abstract. We consider an M/P H/1 queue with deterministic impatience time. An exact analytical expression for the stationary distribution of the workload is derived. By modifying the workload process and using Markovian structure of the phase-type distribution for service times, we are able to construct a new Markov process. The stationary distribution of the new Markov process allows us to find the stationary distribution of the workload. By using the stationary distribution of the workload, we obtain performance measures such as the loss probability, the waiting time distribution and the queue size distribution.

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“…The literature on queueing systems with reneging is moderate. This includes classical works such as [14]- [16] and recent works such as [17]- [20]. Among them, Barrer [14] obtained the reneging probability for deterministic patient time customers.…”

Section: Related Workmentioning

confidence: 99%

“…However, their analysis involves inverse Laplace transformations which does not provide a closed-form expression for the performance parameters. Queueing systems with state-dependent arrival/service rate have been studied in [17], [18]. References [12], [16] mostly focused on steady-state probability distributions of the queue length with reneging customers.…”

Section: Related Workmentioning

confidence: 99%

Multimedia Messaging Service: System Description and Performance Analysis

Ghaderi

Keshav

First International Conference on Wireless Internet (WICON'05)

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Abstract-Following the success of short messaging service (SMS), multimedia messaging service (MMS) is emerging as a natural but revolutionary successor to short messaging. MMS allows personalized multimedia messages containing content such as images, audio, text and video to be created and transferred between MMS-capable phones and other devices. By using IP and its associated protocols, MMS is able to interwork with other messaging systems such as Internet messaging services. An important feature of MMS is the guaranteed delivery of messages via a store-and-forward mechanism which temporarily stores messages in the network until successfully delivered. Unlike SMS, multimedia messaging service does not mandate any maximum size for a multimedia message. This enhanced flexibility of MMS requires a careful design of the network in order to avoid excessive message delays and losses. This paper develops a mathematical model for evaluating the performance of an MMS system. Using the model, closed-form expressions for major performance parameters such as message loss, message delay and expiry probability have been derived. Furthermore, a simple algorithm is presented to find the optimal temporary storage size for a given set of system parameters. The accuracy of the presented analysis is evaluated through simulations which shows a close agreement between analytic and simulation results.

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On queueing with customer impatience until the beginning of service

Cited by 33 publications

References 10 publications

Optimal static priority rules for stochastic scheduling with impatience

Optimal static priority rules for stochastic scheduling with impatience

M/Ph/1 Queue With Deterministic Impatience Time

Multimedia Messaging Service: System Description and Performance Analysis

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