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A Research Roadmap of Big Data Clustering Algorithms for Future Internet of Things

机译:未来事物互联网大数据聚类算法的研究路线图

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摘要

Due to the massive data increase in different Internet of Things (IoT) domains such as healthcare IoT and Smart City IoT, Big Data technologies have been emerged as critical analytics tools for analyzing the IoT data. Among the Big Data technologies, data clustering is one of the essential approaches to process the IoT data. However, how to select a suitable clustering algorithm for IoT data is still unclear. Furthermore, since Big Data technology are still in its initial stage for different IoT domains, it is thus valuable to propose and structure the research challenges between Big Data and IoT. Therefore, this article starts by reviewing and comparing the data clustering algorithms that can be applied in IoT datasets, and then extends the discussions to a broader IoT context such as IoT dynamics and IoT mobile networks. Finally, this article identifies a set of research challenges that harvest a research roadmap for the Big Data research in IoT domains. The proposed research roadmap aims at bridging the research gaps between Big Data and various IoT contexts.
机译:由于不同的数据互联网(IOT)域(如医疗保健物联网和智能城市物联网,大数据技术被出现为分析物联网数据的重要分析工具。在大数据技术中,数据聚类是处理物联网数据的基本方法之一。但是,如何选择适合IOT数据的聚类算法仍然不清楚。此外,由于大数据技术仍处于不同的IOT域的初始阶段,因此提出和构建大数据和物联网之间的研究挑战是有价值的。因此,本文通过审查和比较可以应用于IOT数据集的数据聚类算法,然后将讨论扩展到更广泛的IOT语境,如IOT动态和IOT移动网络。最后,本文识别了一系列研究挑战,从而获得了IOT领域的大数据研究的研究路线图。拟议的研究路线图旨在弥合大数据和各种IOT背景之间的研究差距。

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