Video Big Data Analytics in the Cloud: A Reference Architecture, Survey, Opportunities, and Open Research Issues
Aftab Alam, Irfan Ullah, Young-Koo Lee

TL;DR
This paper provides a comprehensive survey and reference architecture for video big data analytics in the cloud, highlighting current trends, challenges, and future research directions in this rapidly evolving field.
Contribution
It offers the first generalized view of video big data analytics in the cloud, including a layered reference architecture and an extensive review of recent research.
Findings
Proposes a service-oriented layered reference architecture.
Identifies key challenges and open research issues.
Reviews state-of-the-art trends in video big data analytics.
Abstract
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…
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