A Robust Dynamic Edge Network Architecture for the Internet of Things
A Robust Dynamic Edge Network Architecture for the Internet of Things
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DOI：
10.1109/mnet.2018.1700263
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发表时间：
2017-10
期刊：
影响因子：
9.3
通讯作者：
B. Lorenzo;Juan García-Rois;Xuanheng Li;F. González-Castaño;Yuguang Fang
中科院分区：
文献类型：
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作者：
B. Lorenzo;Juan García-Rois;Xuanheng Li;F. González-Castaño;Yuguang Fang
预计大量设备将在具有新应用和连接要求的网络物理物联网系统中完成传感，处理和控制任务。在这种情况下，稀缺的频谱资源必须适应具有低延迟、高可靠性和能量效率的严格要求的高业务量。由于回程链路中的拥塞，传统的集中式网络架构可能无法满足这些要求。本文提出了一种用于物联网的rDNA的新颖设计，该设计利用了移动的设备的最新进展（例如，它们充当接入点的能力、存储和计算能力）以动态地收获未使用的资源并减轻网络拥塞。然而，业务动态可能会损害终端接入点和信道的可用性，从而损害网络连接性。建议的设计包括物理层、接入层、网络层、应用层和业务层的解决方案，以提高网络的鲁棒性。移动的设备的高密度为紧密连接提供了替代方案，减少了干扰和延迟，从而提高了可靠性和能效。此外，移动的设备的计算能力将智能投射到边缘，这对于自主和智能决策是期望的。案例研究包括说明rDNA的性能。概述了这种架构在物联网背景下的潜在应用。最后，提出了未来研究的一些挑战。
A massive number of devices are expected to fulfill the missions of sensing, processing and control in cyber-physical IoT systems with new applications and connectivity requirements. In this context, scarce spectrum resources must accommodate high traffic volume with stringent requirements of low latency, high reliability, and energy efficiency. Conventional centralized network architectures may not be able to fulfill these requirements due to congestion in backhaul links. This article presents a novel design of an RDNA for IoT that leverages the latest advances of mobile devices (e.g., their capability to act as access points, storing and computing capabilities) to dynamically harvest unused resources and mitigate network congestion. However, traffic dynamics may compromise the availability of terminal access points and channels, and thus network connectivity. The proposed design embraces solutions at the physical, access, networking, application, and business layers to improve network robustness. The high density of mobile devices provides alternatives for close connectivity, reducing interference and latency, and thus increasing reliability and energy efficiency. Moreover, the computing capabilities of mobile devices project smartness onto the edge, which is desirable for autonomous and intelligent decision making. A case study is included to illustrate the performance of RDNA. Potential applications of this architecture in the context of IoT are outlined. Finally, some challenges for future research are presented.