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Dyn-ARF: a rate adaptation mechanism sensitive to the network load over 802.11 WLANs

Author

Listed:
  • Maria Angeles Santos

    (Universidad de Castilla-La Mancha)

  • José Miguel Villalón

    (Universidad de Castilla-La Mancha)

  • Luis Orozco-Barbosa

    (Universidad de Castilla-La Mancha)

Abstract

Since the first version of the IEEE 802.11, the standard committee has included a set of transmission rates aiming to accommodate the wide variety of requirements of end-user devices and channel operating conditions. Traditionally, the sender increases the data transmission rate upon receiving various consecutive acknowledgement packets while the data transmission rate is decreased on the absence of acknowledgement packets. This error-control procedure assumes that the channel operating conditions are the main source of transmission errors and losses. However, under medium or high load conditions, transmission impairments are mainly due to channel access conflicts: collisions. Under these load conditions, reducing the data transmission based exclusively on the absence of feedback not only proves ineffective, but it actually degrades the overall network performance. In this paper, we describe a novel rate adaptation mechanism capable of mitigating the effect of collisions using the information imbedded in the received packets. Simulation results show that our proposal limits the use of the data transmission adaptation mechanism which in turn results on a significant increase of the aggregated throughput.

Suggested Citation

  • Maria Angeles Santos & José Miguel Villalón & Luis Orozco-Barbosa, 2016. "Dyn-ARF: a rate adaptation mechanism sensitive to the network load over 802.11 WLANs," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 61(1), pages 5-19, January.
    • Handle: RePEc:spr:telsys:v:61:y:2016:i:1:d:10.1007_s11235-014-9949-5
    DOI: 10.1007/s11235-014-9949-5
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    References listed on IDEAS

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    1. Se-il Mun & Ki-jung Ahn, 2008. "Road Pricing in a Serial Network," Journal of Transport Economics and Policy, University of Bath, vol. 42(3), pages 367-395, September.
    2. D W R Marsh & G Bearfield, 2008. "Generalizing event trees using Bayesian networks," Journal of Risk and Reliability, , vol. 222(2), pages 105-114, June.
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    Cited by:

    1. Mohsen Maadani, 2019. "Reanalyzing a simplified Markov model for the low-density P2P wireless sensor and actuator networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 70(2), pages 159-169, February.

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