1,216 research outputs found

    Load-aware Channel Selection for 802.11 WLANs with Limited Measurement

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    It has been known that load unaware channel selection in 802.11 networks results in high level interference, and can significantly reduce the network throughput. In current implementation, the only way to determine the traffic load on a channel is to measure that channel for a certain duration of time. Therefore, in order to find the best channel with the minimum load all channels have to be measured, which is costly and can cause unacceptable communication interruptions between the AP and the stations. In this paper, we propose a learning based approach which aims to find the channel with the minimum load by measuring only limited number of channels. Our method uses Gaussian Process Regressing to accurately track the traffic load on each channel based on the previous measured load. We confirm the performance of our algorithm by using experimental data, and show that the time consumed for the load measurement can be reduced up to 46% compared to the case where all channels are monitored.Comment: accepted to IC

    Using multiple metrics for rate adaptation algorithms in IEEE 802.11 WLANs

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    A Remote Capacity Utilization Estimator for WLANs

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    In WLANs, the capacity of a node is not fixed and can vary dramatically due to the shared nature of the medium under the IEEE 802.11 MAC mechanism. There are two main methods of capacity estimation in WLANs: Active methods based upon probing packets that consume the bandwidth of the channel and do not scale well. Passive methods based upon analyzing the transmitted packets that avoid the overhead of transmitting probe packets and perform with greater accuracy. Furthermore, passive methods can be implemented locally or remotely. Local passive methods require an additional dissemination mechanism in order to communicate the capacity information to other network nodes which adds complexity and can be unreliable under adverse network conditions. On the other hand, remote passive methods do not require a dissemination mechanism and so can be simpler to implement and also do not suffer from communication reliability issues. Many applications (e.g. ANDSF etc) can benefit from utilizing this capacity information. Therefore, in this thesis we propose a new remote passive Capacity Utilization estimator performed by neighbour nodes. However, there will be an error associated with the measurements owing to the differences in the wireless medium as observed by the different nodes’ location. The main undertaking of this thesis is to address this issue. An error model is developed to analyse the main sources of error and to determine their impact on the accuracy of the estimator. Arising from this model, a number of modifications are implemented to improve the accuracy of the estimator. The network simulator ns2 is used to investigate the performance of the estimator and the results from a range of different test scenarios indicate its feasibility and accuracy as a passive remote method. Finally, the estimator is deployed in a node saturation detection scheme where it is shown to outperform two other similar schemes based upon queue observation and probing with ping packets

    Improving the Performance of Wireless LANs

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    This book quantifies the key factors of WLAN performance and describes methods for improvement. It provides theoretical background and empirical results for the optimum planning and deployment of indoor WLAN systems, explaining the fundamentals while supplying guidelines for design, modeling, and performance evaluation. It discusses environmental effects on WLAN systems, protocol redesign for routing and MAC, and traffic distribution; examines emerging and future network technologies; and includes radio propagation and site measurements, simulations for various network design scenarios, numerous illustrations, practical examples, and learning aids
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