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Cross-Layer Active Predictive Congestion Control Protocol for Wireless Sensor Networks

机译:无线传感器网络的跨层主动预测拥塞控制协议

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摘要

In wireless sensor networks (WSNs), there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC) for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node's neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.
机译:在无线传感器网络(WSN)中,有许多因素可能导致网络拥塞问题,例如多对一通信模式,无线链路相互干扰,网络拓扑动态变化以及节点的内存受限特性。所有这些因素导致网络更容易发生拥塞。在本文中,提出了一种用于提高网络性能的跨层主动预测拥塞控制方案(CL-APCC)。在CL-APCC中采用排队论,根据单节点的内存状态来分析其数据流,并结合对本地网络的平均占用内存大小的分析。它还分析了本地网络的当前数据变化趋势,以预测并在下一个周期主动调整节点的发送速率。为了确保网络的公平性和及时性,根据等待时间,节点邻居数和数据包的原始优先级对IEEE 802.11协议进行了修订,从而动态调整了节点的发送优先级。 CL-APCC的性能通过广泛的仿真实验进行评估。在解决无线传感器网络中的拥塞方面效率更高。此外,很明显,所提出的方案在改善网络的公平性和寿命方面具有显着的优势。

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