智能数据密集型物联网:调查

Bin Xiao, R. Rahmani, Yuhong Li, D. Gillblad, T. Kanter
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引用次数: 7

摘要

物联网范式提出将具有海量异构性质的实体智能连接起来,形成一个复杂性和数量随时间递增的设备和数据的海洋。与一般的大数据或物联网不同,物联网的数据密集型特性带来了一些具体的挑战,如环境动态性和不确定性。因此,需要借助智能技术来解决数据强度带来的问题。直到最近,有许多不同的观点来处理物联网数据和物联网的不同智能使能器,具有不同的贡献和不同的目标。然而,仍有一些问题没有考虑到。本文将对数据密集型物联网问题进行新的调查研究。除此之外,我们还总结了一些没有被强调的影子问题,这些问题对未来很有意义。我们还为智能数据密集型物联网提出了一个扩展的大数据模型来应对这些挑战。
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Intelligent data-intensive IoT: A survey
The IoT paradigm proposes to connect entities intelligently with massive heterogeneous nature, which forms an ocean of devices and data whose complexity and volume are incremental with time. Different from the general big data or IoT, the data-intensive feature of IoT introduces several specific challenges, such as circumstance dynamicity and uncertainties. Hence, intelligence techniques are needed in solving the problems brought by the data intensity. Until recent, there are many different views to handle IoT data and different intelligence enablers for IoT, with different contributions and different targets. However, there are still some issues have not been considered. This paper will provide a fresh survey study on the data-intensive IoT issue. Besides that, we conclude some shadow issues that have not been emphasized, which are interesting for the future. We propose also an extended big data model for intelligent data-intensive IoT to tackle the challenges.
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