arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1609.03363cs.ITcs.NImath.IT
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CONDENSE:面向未来5G的可重构知识获取架构IoT

CONDENSE: A Reconfigurable Knowledge Acquisition Architecture for Future 5G IoT

Dejan Vukobratovic, Dusan Jakovetic, Vitaly Skachek, Dragana Bajovic, Dino Sejdinovic, Gunes Karabulut Kurt, Camilla Hollanti, Ingo Fischer

摘要:

在未来几年,物联网(IoT)将连接数十亿台智能设备,生成并上传大量数据到云端。如果成功提取,数据中隐藏的知识可以显著提高生活质量并促进经济增长。然而,实现高效物联网的一个关键瓶颈是它对现有通信基础设施的压力,需要传输大量数据。为了解决这个问题,我们提出了一种名为Condense的新架构,它将物联网通信基础设施集成到数据分析中。这是通过网络功能计算的通用概念实现的:通信基础设施应该通过精心设计的途中处理积极参与数据分析,而不是仅仅将数据从物联网源传输到云端。我们定义了Condense架构、其基本层以及其组成模块之间的交互。此外,从实现方面,我们描述了如何将Condense集成到第三代合作伙伴计划(3GPP)机器类型通信(MTC)架构中,以及依靠网络功能虚拟化(NFV)和软件定义网络(SDN)在短时间内使其成为实际可行的技术的前景。最后,从理论方面,我们调查的相关文献计算“原子”功能在模拟和数字域,以及在网络上的功能分解,突出的挑战,见解,和未来的方向,利用这些技术在实际的3GPP MTC架构。

英文摘要:

In forthcoming years, the Internet of Things (IoT) will connect billions of smart devices generating and uploading a deluge of data to the cloud. If successfully extracted, the knowledge buried in the data can significantly improve the quality of life and foster economic growth. However, a critical bottleneck for realising the efficient IoT is the pressure it puts on the existing communication infrastructures, requiring transfer of enormous data volumes. Aiming at addressing this problem, we propose a novel architecture dubbed Condense, which integrates the IoT-communication infrastructure into data analysis. This is achieved via the generic concept of network function computation: Instead of merely transferring data from the IoT sources to the cloud, the communication infrastructure should actively participate in the data analysis by carefully designed en-route processing. We define the Condense architecture, its basic layers, and the interactions among its constituent modules. Further, from the implementation side, we describe how Condense can be integrated into the 3rd Generation Partnership Project (3GPP) Machine Type Communications (MTC) architecture, as well as the prospects of making it a practically viable technology in a short time frame, relying on Network Function Virtualization (NFV) and Software Defined Networking (SDN). Finally, from the theoretical side, we survey the relevant literature on computing "atomic" functions in both analog and digital domains, as well as on function decomposition over networks, highlighting challenges, insights, and future directions for exploiting these techniques within practical 3GPP MTC architecture.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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