Smart access point selection for dense WLANs: A use-case

Raschellà, Alessandro; Bouhafs, Faycal; Mackay, Michael; Zachariou, K.; Pilavakis, V.; Georgiades, Michael

doi:10.1109/wcnc.2018.8377439

Cited by 5 publications

(11 citation statements)

References 10 publications

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“…Raschellà et al [13] proposed to select an AP based on the fittingness factor which is a metric reflecting the suitability of the available spectrum resources to the application requirements. Raschellà et al [14] proposed a centralized network framework of the AP selection based on SDN and considered the QoS requirements of the user's data flow.…”

Section: Related Workmentioning

confidence: 99%

AP Selection Scheme Based on Achievable Throughputs in SDN-Enabled WLANs

Peng

He²,

Wang

et al. 2019

IEEE Access

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To ensure an efficient coverage and allow transparent mobility, it is common to find a number of access points (APs) deployed in the neighborhood of each other in current WLANs. A mobile terminal (MT) often has multiple potential APs that it can connect to, and the selection of an appropriate AP becomes an important factor affecting both the network performance and user experience. This paper proposes a new AP selection scheme, which is based on the analysis of achievable normalized throughputs (ANTs) that the MT could obtain in the network. Specifically, we first compute the normalized throughput that characterizes the channel competition among multiple basic service sets (BSSs) as well as MTs within the same BSS. By evaluating ANTs in situations where the MT associates with different APs, the most appropriate AP for the MT can then be selected. Then, we present the implementation of the proposed AP selection scheme under the SDN-WiFi framework, in which the AP selection process can be performed in a software manner. The experimental results show that our computations on ANTs are of high accuracy and the proposed AP selection scheme can achieve a better performance than the existing schemes in terms of both the quality of service of MTs and the fairness among MTs.

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Section: Related Workmentioning

confidence: 99%

AP Selection Scheme Based on Achievable Throughputs in SDN-Enabled WLANs

Peng

He²,

Wang

et al. 2019

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Hence, the selection of an appropriate AP during the association process plays a major role in guaranteeing a fair and balanced allocation of Wi-Fi resources among STAs. A number of contributions can be found in the state of the art dealing with AP allocation aiming to maximize the QoS of a certain Wi-Fi user [1]- [19]. Our solutions presented in [16]- [19] are among the few contributions that try to address the AP allocation challenge while also recognising the heterogeneous QoS demands of STAs.…”

Section: Introductionmentioning

confidence: 99%

“…A number of contributions can be found in the state of the art dealing with AP allocation aiming to maximize the QoS of a certain Wi-Fi user [1]- [19]. Our solutions presented in [16]- [19] are among the few contributions that try to address the AP allocation challenge while also recognising the heterogeneous QoS demands of STAs. These contributions propose association strategies that match the suitability of users' traffic with a particular AP in terms of their QoS demand.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we aim to address these limitations by introducing a novel AP allocation algorithm for dense Wi-Fi networks, which relies on a centralised potential game supported by the SDWN-based framework proposed in [17]- [19]. Due to the dynamic nature of the analysed scenario, the search for an optimal solution to the allocation problem in real time may not be feasible, making the use of suboptimal heuristics mandatory.…”

Section: Introductionmentioning

confidence: 99%

“…In [18] and [19], we proposed a preliminary version of the AP allocation approach based on the potential game, which we have extended in this paper in the facets illustrated in Section 2.…”

Section: Introductionmentioning

confidence: 99%

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