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    黄骏杰, 陈晓江, 刘晨, 房鼎益, 王薇, 尹小燕, 武岳山. 一种基于休眠调度的数据源拥塞控制方法[J]. 计算机研究与发展, 2015, 52(8): 1852-1861. DOI: 10.7544/issn1000-1239.2015.20140668
    引用本文: 黄骏杰, 陈晓江, 刘晨, 房鼎益, 王薇, 尹小燕, 武岳山. 一种基于休眠调度的数据源拥塞控制方法[J]. 计算机研究与发展, 2015, 52(8): 1852-1861. DOI: 10.7544/issn1000-1239.2015.20140668
    Huang Junjie, Chen Xiaojiang, Liu Chen, Fang Dingyi, Wang Wei, Yin Xiaoyan, Wu Yueshan. A Source Data Congestion Control Based on Sleep Schedule[J]. Journal of Computer Research and Development, 2015, 52(8): 1852-1861. DOI: 10.7544/issn1000-1239.2015.20140668
    Citation: Huang Junjie, Chen Xiaojiang, Liu Chen, Fang Dingyi, Wang Wei, Yin Xiaoyan, Wu Yueshan. A Source Data Congestion Control Based on Sleep Schedule[J]. Journal of Computer Research and Development, 2015, 52(8): 1852-1861. DOI: 10.7544/issn1000-1239.2015.20140668

    一种基于休眠调度的数据源拥塞控制方法

    A Source Data Congestion Control Based on Sleep Schedule

    • 摘要: 为了能够长期对监测区域进行持续的数据采集,无线传感网通常运行在休眠调度模式,这种模式使得网络的通信连通性处在动态变化之中,造成一种新的网络拥塞现象——数据源拥塞.这种拥塞问题会造成节点缓存区溢出,从而导致数据丢失,甚至造成节点不响应任何数据转发请求,该问题在传感器异构的无线传感网中表现得更为严重.许多典型的拥塞控制方法是令网络中的数据绕过拥塞节点进行传输,也有一些方法是对拥塞节点的通信速率进行控制,但是以上这些方法无法缓解数据源拥塞的影响.分析影响数据源拥塞的因素,建立了描述节点数据源拥塞概率的传送带模型,提出了一种以降低数据源拥塞概率为目的的节点休眠调度机制(district cooperation schedule, DCS).通过理论推导和实验分析,证明该模型可以较准确地预测数据源拥塞概率,同时DCS可以有效降低数据源拥塞现象的发生.

       

      Abstract: WSNs usually operate in duty-cycle mode for long life time monitoring. This operating mode makes the communication links in dynamic, which will bring a new congestion in the network—source data congestion (SDC). Source data congestion can lead to a WSNs node to get its buffer overflowed, cause data lost and even make no response to any forwarding requirements. This problem will get worse in the sensor heterogeneous WSNs for some nodes may generate data in a burst mode. Many solutions about network congestion only focus on making data forwarding to bypass the congested node, or controlling the traffic rate. These solutions have no help on the source data congestion because this congestion is caused by the improper duty-cycle mode. According to this situation, this paper analyses the fators that influence the source data congestion, and proposes a model, called conveyor belt model, to describe the probability of source data congestion accurately. Besides, based on this model, we propose a dormant schedule method, aiming at decreasing the probability of source data congestion by reconfiguring the sleeping timer of some nodes. Furthermore, our theoretical analysis and extensive simulation show that the model can exactly predict the source data congestion, and our method can decrease the probability of source data congestion significantly.

       

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