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ECCVideo: A Scalable Edge Cloud Collaborative Video Analysis System
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DOI：10.1109/MIS.2022.3214614.png)
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摘要
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Video analysis drives a wide range of applications in the fields of public safety, autonomous vehicles, etc., with the great potential to impact society. Traditional cloud-based approaches are not applicable because of prohibitive bandwidth consumption and high response latency, while simply edge-based video analysis suffers from large computation delay, considering the restricted computing capacity of edge servers. Therefore, in this article, we focus on low-latency edge-cloud collaborative video analytic applications (ECCVApps) by making full use of resources at both the edge and cloud. Particularly, we present an edge-cloud collaborative video analysis system called ECCVideo, to support the unified management of heterogeneous servers and facilitate the development and deployment of large-scale ECCVApps. Under ECCVideo, we design the application architecture of ECCVApps, including presentation paradigm, transparent communication services, and full lifecycle management. To validate the proposed system, a real-time object detection application is deployed on the ECCVideo prototype.
Keyword:
Image edge detection
Servers
Collaboration
Cloud computing
Cameras
Streaming media
Computer architecture
期刊
IF:
6.1
论文数:
1.6K
被引数:
4.5K
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