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BRPL: backpressure RPL for high-throughput and mobile IoTs

机译:BRpL:用于高吞吐量和移动物联网的背压RpL

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摘要

RPL, an IPv6 routing protocol for Low power Lossy Networks (LLNs), is considered to be the de facto routing standard for the Internet of Things (IoT). However, more and more experimental results demonstrate that RPL performs poorly when it comes to throughput and adaptability to network dynamics. This significantly limits the application of RPL in many practical IoT scenarios, such as an LLN with high-speed sensor data streams and mobile sensing devices. To address this issue, we develop BRPL, an extension of RPL, providing a practical approach that allows users to smoothly combine any RPL Object Function (OF) with backpressure routing. BRPL uses two novel algorithms, QuickTheta and QuickBeta, to support time-varying data traffic loads and node mobility respectively. We implement BRPL on Contiki OS, an open-source operating system for the Internet of Things. We conduct an extensive evaluation using both real-world experiments based on the FIT IoT-LAB testbed and large-scale simulations using Cooja over 18 virtual servers on the Cloud. The evaluation results demonstrate that BRPL not only is fully backward compatible with RPL (i.e. devices running RPL and BRPL can work together seamlessly), but also significantly improves network throughput and adaptability to changes in network topologies and data traffic loads. The observed packet loss reduction in mobile networks is, at a minimum, 60% and up to 1000% can be seen in extreme cases.
机译:RPL是用于低功耗有损网络(LLN)的IPv6路由协议,被认为是物联网(IoT)的事实上的路由标准。但是,越来越多的实验结果表明,RPL在吞吐量和对网络动态的适应性方面表现不佳。这极大地限制了RPL在许多实际的IoT场景中的应用,例如具有高速传感器数据流和移动传感设备的LLN。为了解决这个问题,我们开发了RPL的扩展BRPL,它提供了一种实用的方法,允许用户将任何RPL对象功能(OF)与背压路由顺利地结合起来。 BRPL使用两种新颖的算法QuickTheta和QuickBeta来分别支持时变数据流量负载和节点移动性。我们在Contiki OS(用于物联网的开源操作系统)上实现BRPL。我们使用基于FIT IoT-LAB测试平台的真实世界实验和使用Cooja的大规模仿真对Cloud上的18台虚拟服务器进行了广泛的评估。评估结果表明,BRPL不仅与RPL完全向后兼容(即运行RPL和BRPL的设备可以无缝协作),而且还显着提高了网络吞吐量以及对网络拓扑和数据流量负载变化的适应性。在极端情况下,在移动网络中观察到的丢包率降低至少为60%,最高可达1000%。

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  • 作者

    Tahir, YS; Yang, S; McCann;

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  • 年度 2017
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  • 原文格式 PDF
  • 正文语种 English
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