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Throughput optimization of wireless LANs by surrogate model based cognitive decision making

Mostafa Pakparvar (UGent) , Krishnan Chemmangat Manakkal Cheriya (UGent) , Dirk Deschrijver (UGent) , Michael Mehari (UGent) , David Plets (UGent) , Tom Dhaene (UGent) , Jeroen Hoebeke (UGent) , Ingrid Moerman (UGent) , Luc Martens (UGent) and Wout Joseph (UGent)
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Abstract
Large scale growth of wireless networks and the scarcity of the electromagnetic spectrum are imposing more interference to the wireless terminals which jeopardize the Quality of Service offered to the end users. In order to address this kind of performance degradation, this paper proposes a novel experimentally verified cognitive decision engine which aims at optimizing the throughput of IEEE 802.11 links in presence of homogeneous IEEE 802.11 interference. The decision engine is based on a surrogate model that takes the current state of the wireless network as input and makes a prediction of the throughput. The prediction enables the decision engine to find the optimal configuration of the controllable parameters of the network. The decision engine was applied in a realistic interference scenario where utilization of the cognitive decision engine outperformed the case where the decision engine was not deployed by a worst case improvement of more than 100%.
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MLA
Pakparvar, Mostafa, et al. “Throughput Optimization of Wireless LANs by Surrogate Model Based Cognitive Decision Making.” IEEE Wireless Communications and Networking Conference Workshops, 2015, pp. 188–93.
APA
Pakparvar, M., Chemmangat Manakkal Cheriya, K., Deschrijver, D., Mehari, M., Plets, D., Dhaene, T., … Joseph, W. (2015). Throughput optimization of wireless LANs by surrogate model based cognitive decision making. IEEE Wireless Communications and Networking Conference Workshops, 188–193.
Chicago author-date
Pakparvar, Mostafa, Krishnan Chemmangat Manakkal Cheriya, Dirk Deschrijver, Michael Mehari, David Plets, Tom Dhaene, Jeroen Hoebeke, Ingrid Moerman, Luc Martens, and Wout Joseph. 2015. “Throughput Optimization of Wireless LANs by Surrogate Model Based Cognitive Decision Making.” In IEEE Wireless Communications and Networking Conference Workshops, 188–93.
Chicago author-date (all authors)
Pakparvar, Mostafa, Krishnan Chemmangat Manakkal Cheriya, Dirk Deschrijver, Michael Mehari, David Plets, Tom Dhaene, Jeroen Hoebeke, Ingrid Moerman, Luc Martens, and Wout Joseph. 2015. “Throughput Optimization of Wireless LANs by Surrogate Model Based Cognitive Decision Making.” In IEEE Wireless Communications and Networking Conference Workshops, 188–193.
Vancouver
1.
Pakparvar M, Chemmangat Manakkal Cheriya K, Deschrijver D, Mehari M, Plets D, Dhaene T, et al. Throughput optimization of wireless LANs by surrogate model based cognitive decision making. In: IEEE Wireless Communications and Networking Conference Workshops. 2015. p. 188–93.
IEEE
[1]
M. Pakparvar et al., “Throughput optimization of wireless LANs by surrogate model based cognitive decision making,” in IEEE Wireless Communications and Networking Conference Workshops, New Orleans, USA, 2015, pp. 188–193.
@inproceedings{6990340,
  abstract     = {{Large scale growth of wireless networks and the scarcity of the electromagnetic spectrum are imposing more interference to the wireless terminals which jeopardize the Quality of Service offered to the end users. In order to address this kind of performance degradation, this paper proposes a novel experimentally verified cognitive decision engine which aims at optimizing the throughput of IEEE 802.11 links in presence of homogeneous IEEE 802.11 interference. The decision engine is based on a surrogate model that takes the current state of the wireless network as input and makes a prediction of the throughput. The prediction enables the decision engine to find the optimal configuration of the controllable parameters of the network. The decision engine was applied in a realistic interference scenario where utilization of the cognitive decision engine outperformed the case where the decision engine was not deployed by a worst case improvement of more than 100%.}},
  author       = {{Pakparvar, Mostafa and Chemmangat Manakkal Cheriya, Krishnan and Deschrijver, Dirk and Mehari, Michael and Plets, David and Dhaene, Tom and Hoebeke, Jeroen and Moerman, Ingrid and Martens, Luc and Joseph, Wout}},
  booktitle    = {{IEEE Wireless Communications and Networking Conference Workshops}},
  isbn         = {{978-1-4799-8760-3}},
  keywords     = {{IBCN}},
  language     = {{eng}},
  location     = {{New Orleans, USA}},
  pages        = {{188--193}},
  title        = {{Throughput optimization of wireless LANs by surrogate model based cognitive decision making}},
  year         = {{2015}},
}

Web of Science
Times cited: