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Multi-agent learning for multi-channel wireless sensor networks

机译:多通道无线传感器网络的多智能体学习

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An increased bandwidth demand and the problem of interference have resulted in the advent of multi-channel protocols for Wireless Sensor Networks. In this paper, we propose a distributed contention-free multi-channel access scheme. This scheme is based on the parallel rendez-vous principle, which exploits the possibility of concurrent transmissions on different channels in the same collision domain. We describe a multi-agent learning algorithm that resolves all contention in a traffic adaptive manner. Moreover, the medium access resolution is combined with route selection in order to increase the number of parallel transmissions. The results of simulation experiments show that the proposed protocol can outperform McMAC, a state-of-the-art parallel rendez-vous protocol, in terms of throughput and latency.
机译:带宽需求的增加和干扰问题已导致无线传感器网络的多通道协议的出现。在本文中,我们提出了一种分布式的无竞争多信道访问方案。该方案基于并行会聚原理,该原理利用了在同一冲突域中不同信道上并发传输的可能性。我们描述了一种多智能体学习算法,该算法以流量自适应方式解决所有争用。此外,介质访问分辨率与路由选择相结合,以增加并行传输的数量。仿真实验的结果表明,在吞吐量和延迟方面,所提出的协议可以胜过最先进的并行集合协议McMAC。

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