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References
Ahmed A, Ahmed E (2016) A survey on mobile edge computing. In: Proceedings of 10th international conference on intelligent systems and control, Coimbatore, pp 1–8
Bilal K, Erbad A (2017) Edge computing for interactive media and video streaming. In: Proceedings of 2nd international conference on fog and mobile edge computing, Valencia, pp 68–73
Cuervo E et al (2010) MAUI: Making smartphones last longer with code offload. In: Proceedings of the 8th international conference on Mobile systems, applications, and services, San Francisco, pp 49–62
Drolia U et al (2017) Precog: prefetching for image recognition applications at the edge. In: Proceedings of the 2nd ACM/IEEE symposium on edge computing, San Jose, pp 1–13
Esposito C et al (2017) Challenges of connecting edge and cloud computing: a security and forensic perspective. IEEE Cloud Comput 4(2):13–17
Kosta S et al (2012) ThinkAir: dynamic resource allocation and parallel execution in the cloud for mobile code offloading. In: Proceedings of the 31st annual IEEE international conference on computer communications, Orlando, pp 945–953
Lu Z et al (2018) A computing platform for video crowdprocessing using deep learning. In: Proceedings of the 37th annual IEEE international conference on computer communications, Honolulu, pp 1–9
Ran X et al (2018) DeepDecision: a mobile deep learning framework for edge video analytics. In: Proceedings of the 37th annual IEEE international conference on computer communications, Honolulu, pp 1–9
Ren J et al (2018) Distributed and efficient object detection in edge computing: challenges and solutions. IEEE Netw 1–7. https://doi.org/10.1109/MNET.2018.1700415
Salsano S et al (2017) Toward superfluid deployment of virtual functions: exploiting mobile edge computing for video streaming. In: Proceedings of 29th international teletraffic congress, Genoa, pp 48–53
Satyanarayanan M et al (2009) The case for VM-based cloudlets in mobile computing. IEEE Pervasive Comput 8(4):14–23
Satyanarayanan M et al (2015) Edge analytics in the internet of things. IEEE Pervasive Comput 14(2):24–31
Shi W et al (2016) Edge computing: vision and challenges. IEEE Internet Things J 3(5):637–646
Wang D et al (2018) Adaptive wireless video streaming based on edge computing: opportunities and approaches. IEEE Trans Serv Comput 1–12. https://doi.org/10.1109/MNET.2018.1700415
Acknowledgements
This work was supported by the National Natural Science Foundation of China under Grants 61802452, 61572538, Guangdong Special Support Program under Grant 2017TX04X148, the Fundamental Research Funds for the Central Universities under Grant 17LGJC23, and the China Postdoctoral Science Foundation under Grant 2018M631025
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Hu, M., Zhuang, L., Wu, D., Huang, Z., Hu, H. (2019). Edge Computing for Real-Time Video Stream Analytics. In: Shen, X., Lin, X., Zhang, K. (eds) Encyclopedia of Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-32903-1_275-1
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