A dynamic access point allocation algorithm for dense wireless LANs using potential game
Financiación H2020 / H2020 Funds
Resumen: This work introduces an innovative Access Point (AP) allocation algorithm for dense Wi-Fi networks, which relies on a centralised potential game developed in a Software-Defined Wireless Networking (SDWN)-based framework. The proposed strategy optimises the allocation of the Wi-Fi stations (STAs) to APs and allows their dynamic reallocation according to possible changes in the capacity of the Wi-Fi network. This paper illustrates the design of the proposed framework based on SDWN and the implementation of the potential game-based algorithm, which includes two possible strategies. The main novel contribution of this work is that the algorithm allows us to efficiently reallocate the STAs by considering external interference, which can negatively affect the capacities of the APs handled by the SDWN controller. Moreover, the paper provides a detailed performance analysis of the algorithm, which describes the significant improvements achieved with respect to the state of the art. Specifically, the results have been compared against the AP selection considered by the IEEE 802.11 standards and another centralised algorithm dealing with the same problem, in terms of the data bit rate provided to the STAs, their dissatisfaction and Quality of Experience (QoE). Finally, the paper analyses the trade-off between efficient performance and the computational complexity achieved by the strategies implemented in the proposed algorithm.
Idioma: Inglés
DOI: 10.1016/j.comnet.2019.106991
Año: 2020
Publicado en: Computer Networks 167 (2020), 106991 1-12
ISSN: 1389-1286

Factor impacto JCR: 4.474 (2020)
Categ. JCR: COMPUTER SCIENCE, HARDWARE & ARCHITECTURE rank: 9 / 53 = 0.17 (2020) - Q1 - T1
Categ. JCR: TELECOMMUNICATIONS rank: 18 / 91 = 0.198 (2020) - Q1 - T1
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 48 / 273 = 0.176 (2020) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 39 / 162 = 0.241 (2020) - Q1 - T1

Factor impacto SCIMAGO: 0.798 - Computer Networks and Communications (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/T31-17R
Financiación: info:eu-repo/grantAgreement/EC/H2020/644262/EU/What to do With the Wi-Fi Wild West/Wi-5
Financiación: info:eu-repo/grantAgreement/ES/MICINN/RTI2018-099063-B-100
Tipo y forma: Artículo (PostPrint)
Área (Departamento): Área Ingeniería Telemática (Dpto. Ingeniería Electrón.Com.)

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