Edge-cloud collaborative processing for intelligent internet of things: a case study on smart surveillance
Open accessAbstract
Limited processing power and memory prevent realization of state of the art algorithms on the edge level. Offloading computations to the cloud comes with tradeoffs as compression techniques employed to conserve transmission bandwidth and energy adversely impact accuracy of the algorithm. In this paper, we propose collaborative processing to actively guide the output of the sensor to improve performance on the end application. We apply this methodology to smart surveillance specifically the task of object detection from video. Perceptual quality and object detection performance is characterized and improved under a variety of channel conditions.
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Cites
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“Certainly, edge computing and cloud computing are not mutually exclusive [7], [8].”
Background
- Authors
- Mudassar, B. A., Ko, J. H., & Mukhopadhyay, S.
- Affiliations
- Georgia Institute of Technology (US)
- Venue
- Proceedings of the 55th Annual Design Automation Conference
- Publisher
- ACM
- Published
- 2018-06-24
- Pages
- 1-6
- ISSN
- 0738-100X (ISSN-L)
- OpenAlex
- W2808954838
- Cited by
- 20
- References
- 16
- Citations by year
- 2024: 1 · 2023: 4 · 2022: 2 · 2021: 5 · 2020: 1 · 2019: 6 · 2018: 1
- FWCI
- 2.69
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM/IEEE Design Automation Conference (DAC) (publishedVersion)
- Funders
- Defense Advanced Research Projects Agency (HR0011-17-2-0045)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Networks and Communications › Distributed Sensor Networks and Detection Algorithms
- Keywords
- cloud-edge collaboration, cooperative processing, intelligent Internet of Things, computation offloading, video object detection, intelligent surveillance, perceptual quality, channel conditions
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