409 research outputs found

    Evaluations and Enhancements in 802.11n WLANs – Error-Sensitive Adaptive Frame Aggregation

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    IEEE 802.11n is a developing next-generation standard for wireless local area network (LAN). Seamless multimedia traffic connection will become possible with the 802.11n improvement in the Physical and MAC layer. The new 802.11n frame aggregation technique is particularly important for enhancing MAC layer efficiency under high speed wireless LAN. Although the frame aggregation can increase the efficiency in the MAC layer, it does not provide good performance in high BER channels when using large frame aggregation size. An Optimal Frame Aggregation (OFA) technique for AMSDU frame under different BERs in 802.11n WLANs was proposed. However, the suggested algorithm does not take into account the loss rate and the delay performance requirements for Voice or Video multimedia traffic in various BER channels. The optimal frame size can provide good throughput in the network, but the delay might exceed the Quality of Service (QoS) requirement of Voice traffic or the Frame-Error-Rate (FER) might exceed the maximum loss rate tolerable by the streaming Video traffic. We propose an Error- Sensitive Adaptive Frame Aggregation (ESAFA) scheme which can dynamically set the size of AMSDU frame based on the maximum Frame-Error-Rate (FER) tolerable by a particular multimedia traffic. The simulations show that our adaptive algorithm outperforms the optimal frame algorithm by improving both the delay and the loss rate in the 802.11n WLANs. The measured FER of the Error-Sensitive Adaptive Frame Aggregation scheme can be kept at about the same as the loss rate requirement for Video traffic even under high Bit-Error-Rate (BER) channel. The delay compared to OFA is also decreased by around 50% under different channel conditions. Moreover, the results show that the Error-Sensitive Adaptive Frame Aggregation scheme works particularly well in error-prone wireless networks

    Adaptive delayed channel access for IEEE 802.11n WLANs

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    Abstract— In this paper we investigate potential benefits that an adaptive delayed channel access algorithm can attain for the next-generation wireless LANs, the IEEE 802.11n. We show that the performance of frame aggregation introduced by the 802.11n adheres due to the priority mechanism of the legacy 802.11e EDCA scheduler, resulting in a poor overall performance. Because high priority flows have low channel utilization, the low priority flows throughputs can be amerced further. By introducing an additional delay at the MAC layer, before the channel access scheduling, it will retain aggregate sizes at higher numbers and consequently a better channel utilization. Also, in order to support both UDP and TCP transport layer protocols, the algorithm’s operational conditions are kept adaptive. The simulation results demonstrate that our proposed adaptive delayed channel access outperforms significantly the current 802.11n specification and non-adaptive delayed channel access

    Video QoS/QoE over IEEE802.11n/ac: A Contemporary Survey

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    The demand for video applications over wireless networks has tremendously increased, and IEEE 802.11 standards have provided higher support for video transmission. However, providing Quality of Service (QoS) and Quality of Experience (QoE) for video over WLAN is still a challenge due to the error sensitivity of compressed video and dynamic channels. This thesis presents a contemporary survey study on video QoS/QoE over WLAN issues and solutions. The objective of the study is to provide an overview of the issues by conducting a background study on the video codecs and their features and characteristics, followed by studying QoS and QoE support in IEEE 802.11 standards. Since IEEE 802.11n is the current standard that is mostly deployed worldwide and IEEE 802.11ac is the upcoming standard, this survey study aims to investigate the most recent video QoS/QoE solutions based on these two standards. The solutions are divided into two broad categories, academic solutions, and vendor solutions. Academic solutions are mostly based on three main layers, namely Application, Media Access Control (MAC) and Physical (PHY) which are further divided into two major categories, single-layer solutions, and cross-layer solutions. Single-layer solutions are those which focus on a single layer to enhance the video transmission performance over WLAN. Cross-layer solutions involve two or more layers to provide a single QoS solution for video over WLAN. This thesis has also presented and technically analyzed QoS solutions by three popular vendors. This thesis concludes that single-layer solutions are not directly related to video QoS/QoE, and cross-layer solutions are performing better than single-layer solutions, but they are much more complicated and not easy to be implemented. Most vendors rely on their network infrastructure to provide QoS for multimedia applications. They have their techniques and mechanisms, but the concept of providing QoS/QoE for video is almost the same because they are using the same standards and rely on Wi-Fi Multimedia (WMM) to provide QoS

    Experimental Performance Evaluation and Frame Aggregation Enhancement in IEEE 802.11n WLANs

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    The IEEE 802.11n standard promises to extend today’s most popular WLAN standard by significantly increasing reach, reliability, and throughput. Ratified on September 2009, this standard defines many new physical and medium access control (MAC) layer enhancements. These enhancements aim to provide a data transmission rate of up to 600 Mbps. Since June 2007, 802.11n products are available on the enterprise market based on the draft 2.0. In this paper we investigate the effect of most of the proposed 802.11n MAC and physical layer features on the adhoc networks performance. We have performed several experiments in real conditions. The experimental results demonstrated the effectiveness of 802.11n enhancement. We have also examined the interoperability and fairness of 802.11n. The frame aggregation mechanism of 802.11n MAC layer can improve the efficiency of channel utilization by reducing the protocol overheads. We focused on the effect of frame aggregation on the support of voice and video applications in wireless networks. We also propose a new frame aggregation scheduler that considers specific QoS requirements for multimedia applications. We dynamically adjust the aggregated frame size based on frame's access category defined in 802.11e standard

    An Adaptive Packet Aggregation Algorithm (AAM) for Wireless Networks

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    Packet aggregation algorithms are used to improve the throughput performance by combining a number of packets into a single transmission unit in order to reduce the overhead associated with each transmission within a packet-based communications network. However, the throughput improvement is also accompanied by a delay increase. The biggest drawback of a significant number of the proposed packet aggregation algorithms is that they tend to only optimize a single metric, i.e. either to maximize throughput or to minimize delay. They do not permit an optimal trade-off between maximizing throughput and minimizing delay. Therefore, these algorithms cannot achieve the optimal network performance for mixed traffic loads containing a number of different types of applications which may have very different network performance requirements. In this thesis an adaptive packet aggregation algorithm called the Adaptive Aggregation Mechanism (AAM) is proposed which achieves an aggregation trade-off in terms of realizing the largest average throughput with the smallest average delay compared to a number of other popular aggregation algorithms under saturation conditions in wireless networks. The AAM algorithm is the first packet aggregation algorithm that employs an adaptive selection window mechanism where the selection window size is adaptively adjusted in order to respond to the varying nature of both the packet size and packet rate. This algorithm is essentially a feedback control system incorporating a hybrid selection strategy for selecting the packets. Simulation results demonstrate that the proposed algorithm can (a) achieve a large number of sub-packets per aggregate packet for a given delay and (b) significantly improve the performance in terms of the aggregation trade-off for different traffic loads. Furthermore, the AAM algorithm is a robust algorithm as it can significantly improve the performance in terms of the average throughput in error-prone wireless networks
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