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Machine-to-Machine Communications With In-Network Data Aggregation, Processing, and Actuation for Large-Scale Cyber-Physical Systems

机译:具有大型网络物理系统的网络内数据聚合,处理和启动的机器对机器通信

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摘要

Machine-to-Machine (M2M) paradigm enables machines (sensors, actuators, robots, and smart meter readers) to communicate with each other with little or no human intervention. M2M is a key enabling technology for the cyber-physical systems (CPSs). This paper explores CPS beyond M2M concept and looks at futuristic applications. Our vision is CPS with distributed actuation and in-network processing. We describe few particular use cases that motivate the development of the M2M communication primitives tailored to large-scale CPS. M2M communications in literature were considered in limited extent so far. The existing work is based on small-scale M2M models and centralized solutions. Different sources discuss different primitives. Few existing decentralized solutions do not scale well. There is a need to design M2M communication primitives that will scale to thousands and trillions of M2M devices, without sacrificing solution quality. The main paradigm shift is to design localized algorithms, where CPS nodes make decisions based on local knowledge. Localized coordination and communication in networked robotics, for matching events and robots, were studied to illustrate new directions.
机译:机器对机器(M2M)范例使机器(传感器,执行器,机器人和智能电表读取器)之间的通信几乎无需人工干预。 M2M是用于网络物理系统(CPS)的关键启用技术。本文探讨了超越M2M概念的CPS,并探讨了未来应用程序。我们的愿景是具有分布式驱动和网络内处理功能的CPS。我们描述了一些特定的用例,这些用例会激发针对大规模CPS量身定制的M2M通信原语的开发。到目前为止,文献中的M2M通信在有限程度上被考虑。现有工作基于小型M2M模型和集中式解决方案。不同的来源讨论了不同的原语。现有的分散式解决方案很少能很好地扩展。需要设计一种M2M通信原语,该原语可以扩展到成千上万亿个M2M设备,而不会牺牲解决方案质量。主要的范式转移是设计本地化算法,其中CPS节点根据本地知识做出决策。为了匹配事件和机器人,研究了网络机器人中的局部协调和通信,以说明新的方向。

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