Markov-modulated M/G/1 type queue in heavy traffic and its application to time-sharing disciplines

Halldora Thorsdottir (1) , Ina Maria Maaike Verloop (2, 3)

1 Centrum Wiskunde & Informatica and Universiteit of Amsterdam
2 IRIT-RMESS - Réseaux, Mobiles, Embarqués, Sans fil, Satellites
3 CNRS - Centre National de la Recherche Scientifique

This paper deals with a single-server queue with modulated arrivals, service requirements and service capacity. In our first result, we derive the mean of the total workload assuming generally distributed service requirements and any service discipline which does not depend on the modulating environment. We then show that the workload is exponentially distributed under heavy-traffic scaling. In our second result, we focus on the discriminatory processor sharing (DPS) discipline. Assuming exponential, class-dependent service requirements, we show that the joint distribution of the queue lengths of different customer classes under DPS undergoes a state-space collapse when subject to heavy-traffic scaling. That is, the limiting distribution of the queue-length vector is shown to be exponential, times a deterministic vector. The distribution of the scaled workload, as derived for general service disciplines, is a key quantity in the proof of the state-space collapse.

Mots clés: Markov-modulation; Heavy traffic; Discriminatory processor sharing; Single-server queue

Domaines: Réseaux et télécommunications [cs.NI]; Système d'exploitation [cs.OS]; Architectures Matérielles [cs.AR]; Systèmes embarqués

Halldora Thorsdottir, Ina Maria Maaike Verloop. Markov-modulated M/G/1 type queue in heavy traffic and its application to time-sharing disciplines. Queueing Systems, 2016, 83, pp.29-55. ⟨10.1007/s11134-016-9477-y⟩. ⟨hal-02640380⟩