61 research outputs found

    QoS Categories Activeness-Aware Adaptive EDCA Algorithm for Dense IoT Networks

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    IEEE 802.11 networks have a great role to play in supporting and deploying of the Internet of Things (IoT). The realization of IoT depends on the ability of the network to handle a massive number of stations and transmissions, and to support Quality of Service (QoS). IEEE 802.11 networks enable the QoS by applying the Enhanced Distributed Channel Access (EDCA) with static parameters regardless of existing network capacity or which Access Category (AC) of QoS is already active. Our objective in this paper is to improve the efficiency of the uplink access in 802.11 networks; therefore we proposed an algorithm called QoS Categories Activeness-Aware Adaptive EDCA Algorithm (QCAAAE) which adapts Contention Window (CW) size, and Arbitration Inter-Frame Space Number (AIFSN) values depending on the number of associated Stations (STAs) and considering the presence of each AC. For different traffic scenarios, the simulation results confirm the outperformance of the proposed algorithm in terms of throughput (increased on average 23%) and retransmission attempts rate (decreased on average 47%) considering acceptable delay for sensitive delay services.Comment: 17 pages, 10 figure

    Development of a Quality of Service Framework for Multimedia Streaming Applications

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    By the year 2012, it is expected that the majority of all Internet traffic will be video content. Coupled with this is the increasing availability of Wireless Local Area Networks (WLANs) due to their ease of deployment, flexibility and reducing roll out costs. Unfortunately the contention based access mechanism utilised by IEEE 802.11 WLANs does not suit the non-uniform or bursty bandwidth profile of a video stream which can lead to a reduced quality of service (QoS) being experienced by the end-user. In 2005, the IEEE 802.11e protocol was ratified in an attempt to solve this emerging problem. It provides for an access prioritization mechanism based upon four separate traffic classes or access categories (ACs). Each AC is characterised by a set of access parameters that determine its level of access priority which is turn determines the amount of bandwidth available to it. Computer simulation studies have shown that AC prioritisation can yield significant improvements in the QoS delivered over a WLAN. However, these studies have been based upon the use of static access parameters for the ACs. In practice, this is not a viable solution owing to the dynamic and unpredictable nature of the operating conditions on WLANs. In this thesis, an experimental study of AC prioritisation based upon adaptive tuning of the access parameters is presented. This new approach to bandwidth provisioning for video streaming is shown to yield significant improvements in the QoS under a wide range of different operating conditions. For example, it is shown that by adaptively tuning the access control parameters in response to the network conditions, the number of video frames delivered that satisfy QoS requirements is more than doubled

    Introducing reinforcement learning in the Wi-Fi MAC layer to support sustainable communications in e-Health scenarios

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    The crisis of energy supplies has led to the need for sustainability in technology, especially in the Internet of Things (IoT) paradigm. One solution is the integration of Energy Harvesting (EH) technologies into IoT systems, which reduces the amount of battery replacement. However, integrating EH technologies within IoT systems is challenging, and it requires adaptations at different layers of the IoT protocol stack, especially at Medium Access Control (MAC) layer due to its energy-hungry features. Since Wi-Fi is a widely used wireless technology in IoT systems, in this paper, we perform an extensive set of simulations in a dense solar-based energy-harvesting Wi-Fi network in an e-Health environment. We introduce optimization algorithms, which benefit from the Reinforcement Learning (RL) methods to efficiently adjust to the complexity and dynamic behaviour of the network. We assume the concept of Access Point (AP) coordination to demonstrate the feasibility of the upcoming Wi-Fi amendment IEEE 802.11bn (Wi-Fi 8). This paper shows that the proposed algorithms reduce the network&amp;#x2019;s energy consumption by up to 25% compared to legacy Wi-Fi while maintaining the required Quality of Service (QoS) for e-Health applications. Moreover, by considering the specific adjustment of MAC layer parameters, up to 37% of the energy of the network can be conserved, which illustrates the viability of reducing the dimensions of solar cells, while concurrently augmenting the flexibility of this EH technique for deployment within the IoT devices. We anticipate this research will shed light on new possibilities for IoT energy harvesting integration, particularly in contexts with restricted QoS environments such as e-Healthcare.</p

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

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    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.

    Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e

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    This thesis proposes an adaptive traffic prioritization algorithm over ad hoc network using IEEE 802.11e standard that defines a set of Quality of Service enhancements for wireless LAN applications through modifications to the Media Access Control (MAC) layer. The IEEE 802.11e standard aims to provide enhancements that allow traffic with specific requirements to be treated differently from normal traffic. Enhanced Distributed Channel Access (EDCA) is a fundamental and mandatory contention-based channel access method of IEEE 802.11e which delivers traffic based on differentiated Access Category (ACs). Each AC has its own queue and set of EDCA parameter values. Although IEEE 802.11e has been widely implemented in commercial hardware, the EDCA parameters are normally preset with some default values recommended by the standard. By default, the values of EDCA parameters are not open for changes. This has limited the performance as from literature review, a proper EDCA parameter manipulation will improve the network throughput performance. However, most existing research works on IEEE 802.11e EDCA parameter optimization are done either analytically or in simulated environments and hence are unable to provide its effectiveness in realistic scenarios. This is largely due to the several hurdles associated with real-life implementations which prohibit them to do so, such as hardware limitations, software restrictions, coding bugs in the wireless cards driver and so on.These challengess form part of the motivations behind this work. This thesis first investigates the impacts of EDCA parameters on the network performance and link conditions using open source software and commercially available hardware in ad hoc mode. An adaptive prioritization scheme (APS) is then proposed. The results obtained show that the proposed APS algorithm can improve the single-AC throughput performance up to 10.82% when compared to static EDCA. In dual-AC scenario, APS can improve the throughput performance up to 9.93% as compared to static EDCA, while another scheme in existing literature, R-AIFSN shows inconsistency in throughput performance. It is also found that the improvement is more significant in terms of the queue occupancy

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

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    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

    Control-theoretic approaches for efficient transmission on IEEE 802.11e wireless networks

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    With the increasing use of multimedia applications on the wireless network, the functionalities of the IEEE 802.11 WLAN was extended to allow traffic differentiation so that priority traffic gets quicker service time depending on their Quality of Service (QoS) requirements. The extended functionalities contained in the IEEE Medium Access Control (MAC) and Physical Layer (PHY) Specifications, i.e. the IEEE 802.11e specifications, are recommended values for channel access parameters along traffic lines and the channel access parameters are: the Minimum Contention Window CWmin, Maximum Contention Window CWmax, Arbitration inter-frame space number, (AIFSN) and the Transmission Opportunity (TXOP). These default Enhanced Distributed Channel Access (EDCA) contention values used by each traffic type in accessing the wireless medium are only recommended values which could be adjusted or changed based on the condition of number of associated nodes on the network. In particular, we focus on the Contention Window (CW) parameter and it has been shown that when the number of nodes on the network is small, a smaller value of CWmin should be used for channel access in order to avoid underutilization of channel time and when the number of associated nodes is large, a larger value of CWmin should be used in order to avoid large collisions and retransmissions on the network. Fortunately, allowance was made for these default values to be adjusted or changed but the challenge has been in designing an algorithm that constantly and automatically tunes the CWmin value so that the Access Point (AP) gives out the right CWmin value to be used on the WLAN and this value should be derived based on the level of activity experienced on the network or predefined QoS constraints while considering the dynamic nature of the WLAN. In this thesis, we propose the use of feedback based control and we design a controller for wireless medium access. The controller will give an output which will be the EDCA CWmin value to be used by contending stations/nodes in accessing the medium and this value will be based on current WLAN conditions. We propose the use of feedback control due to its established mathematical concepts particularly for single-input-single-output systems and multi-variable systems which are scenarios that apply to the WLAN

    A fuzzy-based QoS Maximization protocol for WiFi Multimedia (IEEE 802.11e) Ad hoc Networks

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    The Quality of Service (QoS) management within a multiple-traffic Wi-Fi MultiMedia (WMM) ad hoc network is a tedious task, since each traffic type requires a well determined QoS-level. For this reason, the IEEE Working Group has proposed the IEEE 802.11e Enhanced Distributed Channel Access (EDCA) protocol at the MAC layer of WMM ad hoc networks. However, several studies have shown that EDCA must be further improved for three main reasons. The first reason is the poor performance of EDCA under high traffic conditions due to the high collision rate. The second reason is the need to maximize the traffic performance (delay, throughput, etc.) guaranteed by EDCA, seen the rapid evolution of the applications (multimedia, real time, etc.). The third reason is the need to maximize the energy efficiency of the EDCA, seen its use in battery constrained devices (e.g. Laptop, Smart phone, Tablet computers, etc.). For these three reasons, we propose in this paper a Three-in-One solution MAC protocol called QoS Maximization of EDCA (QM-EDCA), which is an enhanced version of EDCA. Based on the fuzzy logic mathematic theory, QM-EDCA incorporates a dynamic MAC parameters fuzzy logic system, in order to adapt dynamically the Arbitration inter frame Spaces according to the network state and remaining energy. Simulation results show that QM-EDCA outperforms EDCA by reducing significantly the collision rate, and maximizing traffic performance and energy-efficiency. In addition our solution is fully distributed
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