Color-based Lightweight Utility-aware Load Shedding for Real-Time Video Analytics at the Edge-Reference-Cited by-同舟云学术

Color-based Lightweight Utility-aware Load Shedding for Real-Time Video Analytics at the Edge

Published:2024-06-24 Issue: Volume:1905 Page:123-134
ISSN:
Container-title:Proceedings of the 18th ACM International Conference on Distributed and Event-based Systems
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Author:

Gupta Harshit¹^ORCID,Saurez Enrique¹^ORCID,Röger Henriette²^ORCID,Bhowmik Sukanya³^ORCID,Ramachandran Umakishore⁴^ORCID,Rothermel Kurt²^ORCID

Affiliation:

1. Georgia Institute of Technology, USA and Microsoft Corporation

2. University of Stuttgart, Germany

3. University of Potsdam, Germany

4. Georgia Institute of Technology, USA

Funder

Deutsche Forschungsgemeinschaft

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3629104.3666037

Reference27 articles.

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2. T. T. Le, S. T. Tran, S. Mita, and T. D. Nguyen, "Real time traffic sign detection using color and shape-based features," in Asian Conference on Intelligent Information and Database Systems. Springer, 2010.

3. Wobot.ai. (2021) Team Wobot how is video analytics driving industry 4.0. Wobot Intelligence. [Online]. Available: https://wobot.ai/video-analytics/how-is-video-analytics-driving-industry-4-0/

4. G. Ananthanarayanan, P. Bahl, P. Bodík, K. Chintalapudi, M. Philipose, L. Ravindranath, and S. Sinha, "Real-time video analytics: The killer app for edge computing," computer, vol. 50, no. 10, pp. 58--67, 2017.

5. A Case for Elevating the Edge to be a Peer of the Cloud