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GTXOP: A Game Theoretic Approach for QoS Provisioning Using Transmission Opportunity Tuning

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  • Mahdieh Ghazvini
  • Naser Movahedinia
  • Kamal Jamshidi

Abstract

In unsupervised contention-based networks such as EDCA mode of IEEE 802.11(e)(s), upon winning the channel, each node gets a transmission opportunity (TXOP) in which the node can transmit multiple frames consequently without releasing the channel. Adjusting TXOP can lead to better bandwidth utilization and QoS provisioning. To improve WLAN throughput performance, EDCA packet bursting can be used in 802.11e, meaning that once a station has gained an EDCA-TXOP, it can be allowed to transmit more than one frame without re-contending for the channel. Following the access to the channel, the station can send multiple frames as long as the total access time does not exceed the TXOP Limit. This mechanism can reduce the network overhead and increase the channel utilization instead. However, packet bursting may cause unfairness in addition to increasing jitter, delay and loss. To the best of the authors’ knowledge, although TXOP tuning has been investigated through different methods, it has not been considered within a game theory framework. In this study, based on the analytical models of EDCA, a game theoretic approach called GTXOP is proposed to determine TXOP dynamically (i.e. according to the dynamisms of WLAN networks and the number of nodes in the network). Using GTXOP, each node can choose its TXOP autonomously, such that in addition to QoS improvement, the overall network performance is also improved.

Suggested Citation

  • Mahdieh Ghazvini & Naser Movahedinia & Kamal Jamshidi, 2013. "GTXOP: A Game Theoretic Approach for QoS Provisioning Using Transmission Opportunity Tuning," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-8, May.
    • Handle: RePEc:plo:pone00:0062925
    DOI: 10.1371/journal.pone.0062925
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    Cited by:

    1. Mohammed A Raouf & Fazirulhisyam Hashim & Jiun Terng Liew & Kamal Ali Alezabi, 2020. "Pseudorandom sequence contention algorithm for IEEE 802.11ah based internet of things network," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-34, August.
    2. Gengfa Fang & Mehmet A Orgun & Rajan Shankaran & Eryk Dutkiewicz & Guanglou Zheng, 2016. "Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-19, February.

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