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TORNADO: Intermediate Results Orchestration based Service-Oriented Data Curation Framework for Intelligent Video Big
1Data and Knowledge Engineering Laboratory, Department of Computer Engineering, College of Electronics and Information, Kyung Hee University, 17104, Yongin-si, Gyeonggi-do, Korea.
Sensors (Basel, Switzerland)
|July 1, 2020
Summary
The TORNADO framework offers a scalable cloud solution for intelligent video big data analytics. It enhances distributed video processing, providing researchers with flexible tools for algorithm deployment and improved system performance.
Area of Science:
- Computer Science
- Cloud Computing
- Big Data Analytics
Background:
- Increasing surveillance cameras generate massive video data, necessitating distributed video analytics systems.
- Existing solutions often rely on traditional client/server models, limiting scalability and flexibility.
Purpose of the Study:
- To develop a scalable and flexible framework for intelligent video big data analytics in the cloud.
- To provide high-level abstractions for deploying video analytics algorithms as a service.
Main Methods:
- Developed the TORNADO framework using general-purpose big data technologies.
- Utilized distributed stream and file management systems for acquiring video streams.
- Proposed a unified IR Middleware for orchestrating intermediate analytics results.
Main Results:
- Demonstrated the framework's performance, scalability, and fault tolerance.
- Showcased the viability of the TORNADO framework for cloud-based video big data analytics.
Conclusions:
- The TORNADO framework offers a robust solution for distributed video analytics in the cloud.
- The proposed system improves scalability, fault tolerance, and overall performance for video big data processing.
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