Multi-server preemptive priority queue with general arrivals and service times

Alexandre Brandwajn 1 Thomas Begin 2
2 DANTE - Dynamic Networks : Temporal and Structural Capture Approach
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme, IXXI - Institut Rhône-Alpin des systèmes complexes
Abstract : We present a simple approximate solution for preemptive-resume queues with multiple servers, general (phase-type) service and general (phase-type) interarrival time distributions. In our solution, priority levels are solved one at a time in the order of decreasing priorities. Each priority level is solved approximately using a reduced state description. The complexity of our approximate solution in terms of the number of equations solved grows linearly with the number of servers and priority levels. We studied a large number of numerical examples with a range of values for mean service times and offered loads across priority levels, varying the number of servers from 8 to 48. Discrete-event simulation was used to assess the accuracy of our approximate solution. Overall, in the case of Poisson and quasi-Poisson arrivals, expected relative error for the mean number of customers in the system was below 2% while the corresponding median relative error was below 0.25%. The good accuracy of our approximation appears to extend to the case of phase-type times between arrivals. Our numerical results indicate that the proposed approximation provides a relatively simple and generally accurate approach to preemptive-resume queues with larger numbers of servers and general distributions of service and interarrival times.
Type de document :
[Research Report] RR-9065, Inria - Research Centre Grenoble – Rhône-Alpes. 2017
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Soumis le : vendredi 28 avril 2017 - 14:58:48
Dernière modification le : mercredi 31 octobre 2018 - 12:24:20
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  • HAL Id : hal-01515328, version 1


Alexandre Brandwajn, Thomas Begin. Multi-server preemptive priority queue with general arrivals and service times. [Research Report] RR-9065, Inria - Research Centre Grenoble – Rhône-Alpes. 2017. 〈hal-01515328〉



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