Middleware for Proximity Distributed Real-Time Processing of IoT Data Flows
Middleware for Proximity Distributed Real-Time Processing of IoT Data Flows
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DOI：
10.1109/icdcs.2016.101
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发表时间：
2016-06
期刊：
影响因子：
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通讯作者：
Yugo Nakamura;H. Suwa;Yutaka Arakawa;Hirozumi Yamaguchi;K. Yasumoto
中科院分区：
文献类型：
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作者：
Yugo Nakamura;H. Suwa;Yutaka Arakawa;Hirozumi Yamaguchi;K. Yasumoto
边缘计算和雾计算是新的范例，其中数据处理在网络中或网络边缘上执行，以减轻云服务器负载。然而，EdgeComputing和Fog Computing仍然需要强大的网络边缘服务器，这会增加部署成本。我们提出了一个平台，称为IFoT（信息流的东西），有效地执行分布式处理，以及分布和分析的数据流附近的来源的基础上“处理我们自己（PO 3）”的概念。在IFoT中，云服务器的任务处理被委托给由邻近物联网设备组成的ad-hoc分布式系统，用于分布式实时流处理。在这个演示中，我们展示了一个在IFoT中间件之上开发的用于人员跟踪的人脸识别系统，该中间件通过使用物联网设备的计算资源以实时和分布式的方式本地处理视频流。
EdgeComputing and Fog Computing are new paradigms where data processing is executed in or on the edge of networks to mitigate cloud server load. However, EdgeComputing and Fog Computing still need powerful servers on the edge of networks which impose additional costs for deployments. We proposed a platform called IFoT (Information Flow of Things) that efficiently performs distributed processing as well as distribution and analysis of data streams near their sources based on "Process On Our Own (PO3)" concept. In IFoT, processing of tasks for cloud servers is delegated to an ad-hoc distributed system consisting of proximity IoT devices for distributed real-time stream processing. In this demonstration, we show a face recognition system for person tracking developed on top of IFoT middleware which locally processes video streams in real-time and in a distributed manner by using computational resources of IoT devices.