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To overhear or not to overhear: a dilemma between network coding gain and energy consumption in multi-hop wireless networks

机译:偷听还是不偷听:多跳无线网络中网络编码增益和能耗之间的困境

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Any properly designed network coding technique can result in increased throughput and reliability of multi-hop wireless networks by taking advantage of the broadcast nature of wireless medium. In many inter-flow network coding schemes nodes are encouraged to overhear neighbour's traffic in order to improve coding opportunities at the transmitter nodes. A study of these schemes reveal that some of the overheard packets are not useful for coding operation and thus this forced overhearing increases energy consumption dramatically. In this paper, we formulate network coding aware sleep/wakeup scheduling as a semi Markov decision process (SMDP) that leads to an optimal node operation. In the proposed solution for SMDP, the network nodes learn when to switch off their transceiver in order to conserve energy and when to stay awake to overhear some useful packets. One of the main challenges here is the delay in obtaining reward signals by nodes. We employ a modified reinforcement learning method based on continuous-time Q-learning to overcome this challenge in the learning process. Our simulation results confirm the optimality of the new methodology.
机译:任何适当设计的网络编码技术都可以利用无线媒体的广播特性来提高多跳无线网络的吞吐量和可靠性。在许多流间网络编码方案中,鼓励节点偷听邻居的业务,以改善发射机节点处的编码机会。对这些方案的研究表明,一些偷听的数据包对编码操作没有用,因此这种强制性的偷听行为大大增加了能耗。在本文中,我们将网络编码感知的睡眠/唤醒调度表述为导致最佳节点操作的半马尔可夫决策过程(SMDP)。在为SMDP提出的解决方案中,网络节点学习何时关闭其收发器以节省能量,何时保持清醒以监听一些有用的数据包。这里的主要挑战之一是节点获取奖励信号的延迟。我们采用基于连续时间Q学习的改进强化学习方法来克服学习过程中的这一挑战。我们的仿真结果证实了新方法的最优性。

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