基于物联网应用的大数据增强边缘模型

Pasumpon Pandian A Dr
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引用次数: 32

摘要

边缘计算是云计算的有效替代方案,用于处理时间敏感的任务,已经在广泛的基于物联网的应用中变得非常流行,特别是在工业方面。巨大的信息流和物联网对业务的需求使得传统的云计算在大数据流时代无法兼容。因此,本文提出了一种增强的边缘模型,通过将人工智能与缓存集成到边缘来处理物联网应用中的大数据流。在网络模拟器2中对大量时间敏感任务流的性能评估表明,与传统的云计算模型相比,该方法具有最小的延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ENHANCED EDGE MODEL FOR BIG DATA IN THE INTERNET OF THINGS BASED APPLICATIONS
The edge computing that is an efficient alternative of the cloud computing, for handling of the tasks that are time sensitive, has become has become very popular among a vast range of IOT based application especially in the industrial sides. The huge amount of information flow and the services requisition from the IOT has made the traditional cloud computing incompatible on the time of big data flow. So the paper proposes an enhanced edge model for the by incorporating the artificial intelligence along with the integration of caching to the edge for handling of the big data flow in the applications of the internet of things. The performance evaluation of the same in the network simulator 2 for enormous flow of task that are time sensitive , evinces that the proposed method has a minimized delay compared the traditional cloud computing models.
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