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Queueing analysis of the DRX power saving mechanism in fault-tolerant 3GPP LTE wireless networks

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  • Ioannis Dimitriou

    (Aristotle University of Thessaloniki (A.U.TH.))

Abstract

Energy efficiency and high reliability are major aspects of modern mobile wireless networks. Therefore, it is a critical step to use power management methods along with fault-tolerant techniques. In this paper, we mathematically investigate the Discontinuous Reception, a power saving mechanism in 3GPP LTE wireless networks, with checkpointing and rollback recovery using a variant of an M/G/1 queue with a modified service time and multiple vacations. Due to the lack of enough storage, the mobile device periodically stores its checkpoint data in a stable fixed server, and rolling back to the latest checkpoint when a transient fault or a wireless link error occurs. Various energy and performance metrics are obtained, while constrained optimization problems are formulated and solved. Extensive numerical results are provided, and give an insight into the operation of the model.

Suggested Citation

  • Ioannis Dimitriou, 2016. "Queueing analysis of the DRX power saving mechanism in fault-tolerant 3GPP LTE wireless networks," Annals of Operations Research, Springer, vol. 239(2), pages 521-552, April.
    • Handle: RePEc:spr:annopr:v:239:y:2016:i:2:d:10.1007_s10479-014-1662-y
    DOI: 10.1007/s10479-014-1662-y
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    References listed on IDEAS

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    1. S. C. Borst & O. J. Boxma, 1997. "Polling Models With and Without Switchover Times," Operations Research, INFORMS, vol. 45(4), pages 536-543, August.
    2. S. W. Fuhrmann & Robert B. Cooper, 1985. "Stochastic Decompositions in the M / G /1 Queue with Generalized Vacations," Operations Research, INFORMS, vol. 33(5), pages 1117-1129, October.
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    Cited by:

    1. A. Mohammed Shapique & R. Sudhesh & S. Dharmaraja, 2024. "Transient Analysis of a Modified Differentiated Vacation Queueing System for Energy-Saving in WiMAX," Methodology and Computing in Applied Probability, Springer, vol. 26(3), pages 1-33, September.
    2. Apoorv Saxena & Dieter Claeys & Bo Zhang & Joris Walraevens, 2020. "Cloud data storage: a queueing model with thresholds," Annals of Operations Research, Springer, vol. 293(1), pages 295-315, October.

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