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首页> 外文期刊>IEEE transactions on mobile computing >Robotic Message Ferrying for Wireless Networks Using Coarse-Grained Backpressure Control
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Robotic Message Ferrying for Wireless Networks Using Coarse-Grained Backpressure Control

机译:使用粗粒度反压控制的无线网络机器人消息传递

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We formulate the problem of robots ferrying messages between statically-placed source and sink pairs that they can communicate with wirelessly. We first analyze the capacity region for this problem under ideal conditions. We indicate how robots could be scheduled optimally to satisfy any arrival rate in the capacity region, given prior knowledge about arrival rate. We then consider the setting where the arrival rate is unknown and present a coarse-grained backpressure message ferrying algorithm (CBMF) for it. In CBMF, the robots are matched to sources and sinks once every epoch to maximize a queue-differential-based weight. The matching controls both motion and transmission for each robot. We show through analysis and simulations the conditions under which CBMF can stabilize the network, and its corresponding delay performance. From a practical point of view, we propose a heuristic approach to adapt the epoch duration according to network conditions that can improve the end-to-end delay while guaranteeing the network stability at the same time. We also study the structural properties with its explicit delay performance of the CBMF algorithm in a homogeneous network.
机译:我们提出了机器人在静态放置的源对和接收对之间传递消息的问题,它们可以与之无线通信。我们首先分析理想条件下该问题的能力区域。我们给出了关于到达率的先验知识,从而说明了如何最佳调度机器人以满足容量区域中的任何到达率。然后,我们考虑到达率未知的设置,并为其提供粗粒度背压消息传递算法(CBMF)。在CBMF中,每个时期将机器人与源和汇匹配一次,以最大化基于队列差异的权重。匹配控制每个机器人的运动和传动。通过分析和仿真,我们展示了CBMF可以稳定网络的条件及其相应的延迟性能。从实用的角度出发,我们提出了一种启发式的方法来根据网络条件调整历时长短,从而可以改善端到端延迟,同时保证网络的稳定性。我们还研究了均匀网络中CBMF算法的结构特性及其显式的延迟性能。

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