Edge Enhanced Deep Learning System for Large-Scale Video Stream Analytics

2018 IEEE 2nd International Conference on Fog and Edge Computing, ICFEC 2018 - In conjunction with 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, IEEE/ACM CCGrid 2018

Volumn , Issue , 2018, Pages 1-10

  Ali, Muhammad ^a   Anjum, Ashiq ^a   Usman Yaseen, M ^a   Reza Zamani, A ^b   Balouek Thomert, Daniel ^b   Rana, Omer ^c   Parashar, Manish ^b  

^a UNIVERSITY OF DERBY   (United Kingdom)

^b RUTGERS UNIVERSITY   (United States)

^c CARDIFF UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIG DATA; CLUSTER COMPUTING; DATA HANDLING; EDGE COMPUTING; FOG; GRID COMPUTING; INTERNET OF THINGS; OBJECT RECOGNITION; VIDEO STREAMING;

CLOUD PLATFORMS; COMPUTATIONAL RESOURCES; COMPUTE-INTENSIVE TASKS; EFFICIENCY GAIN; IOT DEVICES; LEARNING MODELS; MACHINE LEARNING MODELS; PROCESSING STAGE;

DEEP LEARNING;

EID: 85048141381     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CFEC.2018.8358733     Document Type: Conference Paper

References (24)

1. G. Fortino, W. Russo, C. Savaglio, W. Shen, and M. Zhou, "Agentoriented cooperative smart objects: From iot system design to implementation, " IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017.
2. C. V. networking Index, "Forecast and methodology, 2016-2021, white paper, " San Jose, CA, USA, vol. 1, 2016.
3. W. Shi, J. Cao, Q. Zhang, Y. Li, and L. Xu, "Edge computing: Vision and challenges, " IEEE Internet of Things Journal, vol. 3, no. 5, pp. 637-646, 2016.
4. G. Ananthanarayanan, P. Bahl, P. Bod?k, 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. C. Regazzoni, A. Cavallaro, Y. Wu, J. Konrad, and A. Hampapur, "Video analytics for surveillance: Theory and practice [from the guest editors], " IEEE Signal Processing Magazine, vol. 27, no. 5, pp. 16-17, 2010.
6. S. John Walker, "Big data: A revolution that will transform how we live, work, and think, " 2014.
7. M. U. Yaseen, A. Anjum, and N. Antonopoulos, "Modeling and analysis of a deep learning pipeline for cloud based video analytics, " in Proceedings of the Fourth IEEE/ACM International Conference on Big Data Computing, Applications and Technologies. ACM, 2017, pp. 121-130.
8. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica et al., "A view of cloud computing, " Communications of the ACM, vol. 53, no. 4, pp. 50-58, 2010.
9. C. Shan, F. Porikli, T. Xiang, and S. Gong, Video Analytics for Business Intelligence. Springer, 2012.
10. H. Liu, S. Chen, and N. Kubota, "Intelligent video systems and analytics: A survey, " IEEE Transactions on Industrial Informatics, vol. 9, no. 3, pp. 1222-1233, 2013.
11. M. U. Yaseen, A. Anjum, and N. Antonopoulos, "Spatial frequency based video stream analysis for object classification and recognition in clouds, " in 2016 IEEE/ACM 3rd International Conference on Big Data Computing Applications and Technologies (BDCAT), Dec 2016, pp. 18-26.
12. R. McClatchey, A. Anjum, H. Stockinger, A. Ali, I. Willers, and M. Thomas, "Data intensive and network aware (diana) grid scheduling, " Journal of Grid computing, vol. 5, no. 1, pp. 43-64, 2007.
13. A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei, "Large-scale video classification with convolutional neural networks, " in Proceedings of the IEEE conference on Computer Vision and Pattern Recognition, 2014, pp. 1725-1732.
14. F. Bonomi, R. Milito, J. Zhu, and S. Addepalli, "Fog computing and its role in the internet of things, " in Proceedings of the first edition of the MCC workshop on Mobile cloud computing. ACM, 2012, pp. 13-16.
15. M. Satyanarayanan, P. Simoens, Y. Xiao, P. Pillai, Z. Chen, K. Ha, W. Hu, and B. Amos, "Edge analytics in the internet of things, " IEEE Pervasive Computing, vol. 14, no. 2, pp. 24-31, 2015.
16. Q. Zhang, Z. Yu, W. Shi, and H. Zhong, "Demo abstract: Evaps: Edge video analysis for public safety, " in Edge Computing (SEC), IEEE/ACM Symposium on. IEEE, 2016, pp. 121-122.
17. A. R. Zamani, M. Zou, J. Diaz-Montes, I. Petri, O. Rana, A. Anjum, and M. Parashar, "Deadline constrained video analysis via in-transit computational environments, " IEEE Transactions on Services Computing, 2017.
18. M. U. Yaseen, A. Anjum, O. Rana, and R. Hill, "Cloud-based scalable object detection and classification in video streams, " Future Generation Computer Systems, vol. 80, pp. 286-298, 2018. [Online]. Available: http://www. sciencedirect. com/science/article/pii/ S0167739X17301929
19. A. Anjum, T. Abdullah, M. Tariq, Y. Baltaci, and N. Antonopoulos, "Video stream analysis in clouds: An object detection and classification framework for high performance video analytics, " IEEE Transactions on Cloud Computing, 2016.
20. Cisco, "Krikkit open source software, " http://www. eclipse. org/ proposals/technology. krikkit, accessed: 2017-12-15.
21. T. G. Robertazzi, "Software-defined networking, " in Introduction to Computer Networking. Springer, 2017, pp. 81-87.
22. N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford, S. Shenker, and J. Turner, "Openflow: enabling innovation in campus networks, " ACM SIGCOMM Computer Communication Review, vol. 38, no. 2, pp. 69-74, 2008.
23. S. Srinivas, R. K. Sarvadevabhatla, K. R. Mopuri, N. Prabhu, S. S. Kruthiventi, and R. V. Babu, "A taxonomy of deep convolutional neural nets for computer vision, " arXiv preprint arXiv:1601. 06615, 2016.
24. R. Laganière, OpenCV 3 Computer Vision Application Programming Cookbook. Packt Publishing Ltd, 2017.