Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Video Big Data Analytics in the Cloud: A Reference Architecture, Survey,
  Opportunities, and Open Research Issues   The proliferation of multimedia devices over the Internet of Things (IoT)
generates an unprecedented amount of data. Consequently, the world has stepped
into the era of big data. Recently, on the rise of distributed computing
technologies, video big data analytics in the cloud has attracted the attention
of researchers and practitioners. The current technology and market trends
demand an efficient framework for video big data analytics. However, the
current work is too limited to provide a complete survey of recent research
work on video big data analytics in the cloud, including the management and
analysis of a large amount of video data, the challenges, opportunities, and
promising research directions. To serve this purpose, we present this study,
which conducts a broad overview of the state-of-the-art literature on video big
data analytics in the cloud. It also aims to bridge the gap among large-scale
video analytics challenges, big data solutions, and cloud computing. In this
study, we clarify the basic nomenclatures that govern the video analytics
domain and the characteristics of video big data while establishing its
relationship with cloud computing. We propose a service-oriented layered
reference architecture for intelligent video big data analytics in the cloud.
Then, a comprehensive and keen review has been conducted to examine
cutting-edge research trends in video big data analytics. Finally, we identify
and articulate several open research issues and challenges, which have been
raised by the deployment of big data technologies in the cloud for video big
data analytics. To the best of our knowledge, this is the first study that
presents the generalized view of the video big data analytics in the cloud.
This paper provides the research studies and technologies advancing video
analyses in the era of big data and cloud computing.

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The categories of this paper are: math-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-th
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The categories of this paper are: stat
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The categories of this paper are: q-alg
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The categories of this paper are: q-fin
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The categories of this paper are: mtrl-th
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The categories of this paper are: gr-qc
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The categories of this paper are: astro-ph
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The categories of this paper are: funct-an
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The categories of this paper are: physics
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The categories of this paper are: comp-gas
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The categories of this paper are: chao-dyn