A New Markov Model for Non-Saturated 802.11 Networks
A New Markov Model for Non-Saturated 802.11 Networks
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DOI：
10.1109/ccnc08.2007.100
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发表时间：
2008-02
期刊：
影响因子：
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通讯作者：
Trong Nghia Dao;R. Malaney
中科院分区：
文献类型：
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作者：
Trong Nghia Dao;R. Malaney
本文为分布式协调函数（DCF）协议引入了一种新的马尔可夫模型，该模型可以准确地预测802.11网络在实际流量负载下的网络吞吐量。具体来说，我们提供了一种改进的后回退处理方法，DIFS后立即传输的概率，以及后回退后有一个新数据包用于传输的概率。我们模型的一个关键特征是能够预测最佳网络吞吐量和网络容量（根据具有可接受QoS的站点数量）。了解网络容量有助于多媒体应用程序的网络规划和QoS。另一个特点是当台站数量增大时，模型收敛于饱和模型。在此基础上，提出了一种估计网络容量下界的新方法。
In this work, we introduce a new Markov model for the distributed coordination function (DCF) protocol which accurately predicts the network throughput of 802.11 networks under realistic traffic load. Specifically, we provide an improved treatment of the post backoff, the probability of immediate transmission after DIFS, and the probability of having a new packet for transmission after the post backoff. A key feature of our model is the ability to predict the optimal network throughput and the network capacity (in terms of number of stations with acceptable QoS). Knowledge of the network capacity aids to network planning and QoS for multimedia applications. Another feature is that the model converges to a saturated model when the number of stations becomes large. Based on this feature, we introduce a new method to estimate the lower bound of network capacity.