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Evaluation of IoT stream processing at edge computing layer for semantic data enrichment

机译:评估边缘计算层的IoT流处理以丰富语义数据

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摘要

The fast development of Internet of Things (IoT) computing and technologies has prompted a decentralization of Cloud-based systems. Indeed, sending all the information from IoT devices directly to the Cloud is not a feasible option for many applications with demanding requirements on real-time response, low latency, energy-aware processing and security. Such decentralization has led in a few years to the proliferation of new computing layers between Cloud and IoT, known as Edge computing layer, which comprises of small computing devices (e.g. Raspberry Pi) to larger computing nodes such as Gateways, Road Side Units, Mini Clouds, MEC Servers, Fog nodes, etc. In this paper, we study the challenges of processing an IoT data stream in an Edge computing layer. By using a real life data stream set arising from a car data stream as well as a real infrastructure using Raspberry Pi and Node-Red server, we highlight the complexities of achieving real time requirements of applications based on IoT stream processing.
机译:物联网(IoT)计算和技术的快速发展促使基于云的系统分散化。实际上,对于许多对实时响应,低延迟,能源感知处理和安全性有苛刻要求的应用而言,将所有信息从IoT设备直接发送到云并不是可行的选择。这种分散化导致了几年后云和物联网之间新的计算层(称为边缘计算层)的激增,它由小型计算设备(例如Raspberry Pi)到较大的计算节点(例如网关,路边单元,小型)组成云,MEC服务器,雾节点等。在本文中,我们研究了在Edge计算层中处理IoT数据流的挑战。通过使用来自汽车数据流的真实数据流集以及使用Raspberry Pi和Node-Red服务器的真实基础架构,我们强调了基于IoT流处理实现应用程序实时需求的复杂性。

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