A Dynamic Multimedia User-Weight Classification Scheme for IEEE_802.11 WLANs

In this paper we expose a dynamic traffic-classification scheme to support multimedia applications such as voice and broadband video transmissions over IEEE 802.11 Wireless Local Area Networks (WLANs). Obviously, over a Wi-Fi link and to better serve these applications - which normally have strict bounded transmission delay or minimum link rate requirement - a service differentiation technique can be applied to the media traffic transmitted by the same mobile node using the well-known 802.11e Enhanced Distributed Channel Access (EDCA) protocol. However, the given EDCA mode does not offer user differentiation, which can be viewed as a deficiency in multi-access wireless networks. Accordingly, we propose a new inter-node priority access scheme for IEEE 802.11e networks which is compatible with the EDCA scheme. The proposed scheme joins a dynamic user-weight to each mobile station depending on its outgoing data, and therefore deploys inter-node priority for the channel access to complement the existing EDCA inter-frame priority. This provides efficient quality of service control across multiple users within the same coverage area of an access point. We provide performance evaluations to compare the proposed access model with the basic EDCA 802.11 MAC protocol mode to elucidate the quality improvement achieved for multimedia communication over 802.11 WLANs.Comment: 15 pages, 8 figures, 3 tables, International Journal of Computer Networks & Communications (IJCNC

Usage of Network Simulators in Machine-Learning-Assisted 5G/6G Networks

Without any doubt, Machine Learning (ML) will be an important driver of future communications due to its foreseen performance when applied to complex problems. However, the application of ML to networking systems raises concerns among network operators and other stakeholders, especially regarding trustworthiness and reliability. In this paper, we devise the role of network simulators for bridging the gap between ML and communications systems. In particular, we present an architectural integration of simulators in ML-aware networks for training, testing, and validating ML models before being applied to the operative network. Moreover, we provide insights on the main challenges resulting from this integration, and then give hints discussing how they can be overcome. Finally, we illustrate the integration of network simulators into ML-assisted communications through a proof-of-concept testbed implementation of a residential Wi-Fi network

A control theoretic approach to achieve proportional fairness in 802.11e EDCA WLANs

This paper considers proportional fairness amongst ACs in an EDCA WLAN for provision of distinct QoS requirements and priority parameters. A detailed theoretical analysis is provided to derive the optimal station attempt probability which leads to a proportional fair allocation of station throughputs. The desirable fairness can be achieved using a centralised adaptive control approach. This approach is based on multivariable statespace control theory and uses the Linear Quadratic Integral (LQI) controller to periodically update CWmin till the optimal fair point of operation. Performance evaluation demonstrates that the control approach has high accuracy performance and fast convergence speed for general network scenarios. To our knowledge this might be the first time that a closed-loop control system is designed for EDCA WLANs to achieve proportional fairness

Adaptive medium access control for VoIP services in IEEE 802.11 WLANs

Abstract- Voice over Internet Protocol (VoIP) is an important service with strict Quality-of-Service (QoS) requirements in Wireless Local Area Networks (WLANs). The popular Distributed Coordination Function (DCF) of IEEE 802.11 Medium Access Control (MAC) protocol adopts a Binary Exponential Back-off (BEB) procedure to reduce the packet collision probability in WLANs. In DCF, the size of contention window is doubled upon a collision regardless of the network loads. This paper presents an adaptive MAC scheme to improve the QoS of VoIP in WLANs. This scheme applies a threshold of the collision rate to switch between two different functions for increasing the size of contention window based on the status of network loads. The performance of this scheme is investigated and compared to the original DCF using the network simulator NS-2. The performance results reveal that the adaptive scheme is able to achieve the higher throughput and medium utilization as well as lower access delay and packet loss probability than the original DCF

Spectrum Utilization and Congestion of IEEE 802.11 Networks in the 2.4 GHz ISM Band

Wi-Fi technology, plays a major role in society thanks to its widespread availability, ease of use and low cost. To assure its long term viability in terms of capacity and ability to share the spectrum efficiently, it is of paramount to study the spectrum utilization and congestion mechanisms in live environments. In this paper the service level in the 2.4 GHz ISM band is investigated with focus on todays IEEE 802.11 WLAN systems with support for the 802.11e extension. Here service level means the overall Quality of Service (QoS), i.e. can all devices fulfill their communication needs? A crosslayer approach is used, since the service level can be measured at several levels of the protocol stack. The focus is on monitoring at both the Physical (PHY) and the Medium Access Control (MAC) link layer simultaneously by performing respectively power measurements with a spectrum analyzer to assess spectrum utilization and packet sniffing to measure the congestion. Compared to traditional QoS analysis in 802.11 networks, packet sniffing allows to study the occurring congestion mechanisms more thoroughly. The monitoring is applied for the following two cases. First the influence of interference between WLAN networks sharing the same radio channel is investigated in a controlled environment. It turns out that retry rate, Clear-ToSend (CTS), Request-To-Send (RTS) and (Block) Acknowledgment (ACK) frames can be used to identify congestion, whereas the spectrum analyzer is employed to identify the source of interference. Secondly, live measurements are performed at three locations to identify this type of interference in real-live situations. Results show inefficient use of the wireless medium in certain scenarios, due to a large portion of management and control frames compared to data content frames (i.e. only 21% of the frames is identified as data frames)