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

An Enhanced scheduling algorithm for QoS optimization in 802.11e based Networks

Quality of Service (QoS) is the ability to guarantee a certain level of performance to a data flow ie., guaranteeing required bit rate, delay, etc. IEEE 802.11 a/b/g networks do not provide QoS differentiation among multimedia traffic. QoS provisioning is one of the essential features in IEEE 802.11e. It uses Enhanced Distributed Channel Access (EDCA) which is a contention-based channel access mode to provide QoS differentiation. EDCA works with four Access Categories (AC). Differentiation of Access Categories are achieved by differentiating the Arbitration Inter-Frame Space (AIFS), the initial contention window size (CWmin), the maximum contention window size (CWmax) and the transmission opportunity (TXOP). However AIFS, CWmin, CWmax are considered to be fixed for a given AC, while TXOP may be varied. A TXOP is a time period when a station has the right to initiate transmissions onto the wireless medium. By varying the TXOP value among the ACs the QoS optimization- throughput stability and minimum delay is achieved. EDCA has many advantages such as it fully utilizes the channel bandwidth, and does not require centralized admission control and scheduling algorithms over the contention-free access mode

A Comprehensive Study of the Enhanced Distributed Control Access (EDCA) Function

This technical report presents a comprehensive study of the Enhanced Distributed Control Access (EDCA) function defined in IEEE 802.11e. All the three factors are considered. They are: contention window size (CW), arbitration inter-frame space (AIFS), and transmission opportunity limit (TXOP). We first propose a discrete Markov chain model to describe the channel activities governed by EDCA. Then we evaluate the individual as well as joint effects of each factor on the throughput and QoS performance. We obtain several insightful observations showing that judiciously using the EDCA service differentiation mechanism is important to achieve maximum bandwidth utilization and user-specified QoS performance. Guided by our theoretical study, we devise a general QoS framework that provides QoS in an optimal way. The means of realizing the framework in a specific network is yet to be studied

A fair access mechanism based on TXOP in IEEE 802.11e wireless networks

IEEE 802.11e is an extension of IEEE 802.11 that provides Quality of Service (QoS) for the applications with different service requirements. This standard makes use of several parameters such as contention window; inter frame space time and transmission opportunity to create service differentiation in the network. Transmission opportunity (TXOP), that is the focus point of this paper, is the time interval, during which a station is allowed to transmit packets without any contention. As the fixed amounts of TXOPs are allocated to different stations, unfairness appears in the network. And when users with different data rates exist, IEEE 802.11e WLANs face the lack of fairness in the network. Because the higher data rate stations transfer more data than the lower rate ones. Several mechanisms have been proposed to solve this problem by generating new TXOPs adaptive to the network's traffic condition. In this paper, some proposed mechanisms are evaluated and according to their evaluated strengths and weaknesses, a new mechanism is proposed for TXOP determination in IEEE 802.11e wireless networks. Our new algorithm considers data rate, channel error rate and data packet lengths to calculate adaptive TXOPs for the stations. The simulation results show that the proposed algorithm leads to better fairness and also higher throughput and lower delays in the network.

Setting the parameters right for two-hop IEEE 802.11e ad hoc networks

Two-hop ad-hoc networks, in which some nodes forward traffic for multiple sources, with which they also compete for channel access suffer from large queues building up in bottleneck nodes. This problem can often be alleviated by using IEEE 802.11e to give preferential treatment to bottleneck nodes. Previous results have shown that differentiation parameters can be used to allocate capacity in a more efficient way in the two-hop scenario. However, the overall throughput of the bottleneck may differ considerably, depending on the differentiation method used. By applying a very fast and accurate analysis method, based on steady-state analysis of an QBD-type infinite Markov chain, we find the maximum throughput that is possible per differentiation parameter. All possible parameter settings are explored with respect to the maximum throughput conditioned on a maximum buffer occupancy. This design space exploration cannot be done with network simulators like NS2 or Opnet, as each simulation run simply takes to long.\ud The results, which have been validated by detailed simulations, show that by differentiating TXOP it is possible to achieve a throughput that is about 50% larger than when differentiating AIFS and CW_min.\u

Analysis of Impact in the Wi-Fi QoS of the EDCA Parameters

With the continuing development of the wireless technologies (Wi-Fi, 3G, 4G, WiMax and Bluethooth), the study of wireless multimedia transmissions has gained lately more attention. For example, the expectations of the company leaders on the growth of Wi-Fi video traffic has updated the lines of research on the standard IEEE 802.11e introduced to provide QoS (Quality of Service) to WLAN (Wireless LAN ) networks. In this paper we updated with greater accuracy, using other resources and the experience gained since the emergence of the standard, the work carried out previously on the quantitative impact of each EDCA (Enhanced Distributed Channel Access) parameter on the overall performance of the mechanisms MAC. A quantitative analysis of the optimizations that can be achieved has been performed by simulation. We use a node model EDCA 802.11e with the tool Möbius of the University of Illinois, which supports an extension of SPN (Stochastic Petri Networks), known as HSAN (Hierarchical Stochastic Activity Networks), what favors the contrast with other tools or mathematical resources. We use a realistic scenario formed by Wi-Fi stations with the capacity to transmit voice, video and best effort traffic. The results show that the default setting of EDCA parameters is not optimal, and that with an appropriate selection, very significant improvements can be obtained. Keywords: QoS, WLAN, EDCA 802.11e, MAC Parameters, Analysis of traffi

Link quality based EDCA MAC protocol for WAVE vehicular networks

The WAVE vehicular networks adopt the Enhanced Distributed Channel Access (EDCA) as the MAC layer protocol. In EDCA, different values of arbitrary inter-frame space (AIFS) can be used for different classes of traffic. The smaller the AIFS value is, the higher the priority a device has in accessing the shared channel. In this paper, we exploit the possibility of assigning the AIFS values according to channel/link quality. Notably a device with better link quality can transmit at a higher data rate. Therefore, our key objective is to maximize the system throughput between a roadside unit (RSU) and the onboard units (OBUs) passed by. Since IEEE 802.11p supports eight transmission rates, two schemes for mapping AIFS values to transmission rates are studied. The first one (8-level-AIFS) uses eight distinct AIFS values, one for each transmission rate. And the second one (4-level-AIFS) uses four distinct AIFS values, one for every two adjacent transmission rates. Their throughput performances are studied by simulations. It is interesting to note that OBUs tend to experience the same pattern of channel quality fluctuation, due to the similar vehicle moving pattern. To this end, assigning AIFS values according to link quality is fair. © 2013 IEEE.published_or_final_versio