Читать книгу The Smart Cyber Ecosystem for Sustainable Development - Группа авторов - Страница 62

Administrators of WLANs normally deploy large number of APs to cover an area and provide users best QoS. In such scenario, a user could be under the coverage of multiple APs and thus has the potential to select the AP to which it will connect. The selection of AP is important and affects the performance a user might experience in the network as well as the overall network performance. This is because wireless networks are highly dynamic, whereas the activation of a link between a user and an AP may influence other ongoing connections in same and/or neighboring cells. In current implementations of WLANs technology, a user selects an AP from which it gets the strongest signal during a scanning phase. It has been shown in large number of research studies that the legacy selection policy does not ensure best QoS for network users. Obviously, an AP to which a user has the strongest connection might be serving large number of users; hence, its cell will be highly congested [48].

The authors of [49] propose an SDN-based AP selection scheme for WLANs. The selection is based on the analysis of achievable throughput a user might get from potential cells. The system computes the throughputs that capture the channel competition among neighboring cells. Some cells may obtain few chances to get the channel. Even in the same cell, mobile users compete with each other for channel access. The authors noticed that the airtime completion and airtime share among WLAN users play a fundamental role in determining the QoS the user will get. The authors implemented their proposed method in an SDN framework comprised of three planes: data plane, CP, and service plane. The data plane consists of a number of thin APs that are responsible for data forwarding. The CP contains a SDN-WiFi controller, while the service plane contains a set of applications such as association control, load balance, and seamless mobility management. The proposed AP selection scheme is implemented in the service plane. The applications are installed on the SDN controller, which collects necessary information from networking devices and decides the best cell for each of newly joining users.

In [50], the authors developed ML-based methods for detecting causes of unnecessary active scanning in WLANs. The authors argue that ML provides the best way to detect causes of unnecessary active scan in WLANs, where various independent and dependent parameters interact together. Both unsupervised and supervised methods are compared.

Data collected from real WLANs is used to train the ML algorithms. The authors deduced that a multilayer perceptron-based classifier model outperforms other models and accurately detect the cause of unnecessary active scanning.

The work in [51] proposes an SDN-based framework for AP selection in WLANs, considering the QoS level required by users’ flows. The authors of [52] study the user association issue in an SDN–architecture. They developed heuristic algorithms that lead to high performance assuming unsaturated heterogeneous Markovian analytical model.

The authors of [53] propose an admission control mechanism for VoIP calls in WLANs. A ML algorithm is used to predict the voice quality considering different parameters at the data link layer such as fraction of channel time used for video and normal traffic as well as estimated frame error rate for video and normal traffic.

The authors of [54] leverage on the SDN paradigm to develop an algorithm that achieves effective distribution of traffic load in WLANs. The authors try to optimally distribute network resources and improve the overall performance.