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Modeling Power Saving Protocols for Multicast Services in 802.11 Wireless LANs

机译:802.11无线局域网中的多播服务节能协议建模

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摘要

In recent years, a series of power saving (PS) protocols has been proposed in the family of 802.11 standards to save energy for mobile devices. To evaluate their performance, many works have been carried out on testbeds or simulation platforms. However, till now, there is a lack of accurate theoretical models to analyze the performance for these protocols. In an effort to fill this gap, we present a Markov chain-based analytical model in this paper to model these PS protocols, with its focus on multicast services in wireless LANs. The proposed analytical model successfully captures the key characteristic of the power saving system: the data delivery procedure starts periodically at the previously negotiated time, but ends at a rather random time with its distribution depending on the end time of data delivery in the last delivery period as well as the arrival rate of incoming traffic. In the situations with light to moderate traffic loads and under the Poisson assumption for incoming traffic, the amount of data delivered between consecutive delivery periods possesses the Markov property, which builds up our Markov chain-based model. For incoming traffic with long-range dependence (LRD), a multistate Markov-Modulated Poisson Process (MMPP) is used to approximate the traffic, making the analytical model valid in more general cases. We verify our model by simulations on ns2 and the results show that the model can faithfully predict the performance of these PS protocols over a wide variety of testing scenarios.
机译:近年来,在802.11标准家族中提出了一系列节能(PS)协议,以节省移动设备的能源。为了评估其性能,已经在测试平台或仿真平台上进行了许多工作。但是,直到现在,仍缺乏准确的理论模型来分析这些协议的性能。为了填补这一空白,我们在本文中提出了一种基于马尔可夫链的分析模型来为这些PS协议建模,其重点是无线局域网中的多播服务。所提出的分析模型成功地捕获了节电系统的关键特征:数据传送过程在先前协商的时间定期开始,但在相当随机的时间结束,其分布取决于最后一次传送周期中数据传送的结束时间以及传入流量的到达率。在轻到中度流量负载的情况下,以及在对传入流量进行泊松假设的情况下,连续交付期间之间交付的数据量具有Markov属性,从而建立了基于Markov链的模型。对于具有长期依赖关系(LRD)的传入流量,使用多状态马尔可夫调制泊松过程(MMPP)来估算流量,从而使分析模型在更一般的情况下有效。我们通过在ns2上进行仿真验证了我们的模型,结果表明该模型可以在各种测试场景下忠实地预测这些PS协议的性能。

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