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2019 | OriginalPaper | Buchkapitel

Latency Control for Distributed Machine Vision at the Edge Through Approximate Computing

verfasst von : Anjus George, Arun Ravindran

Erschienen in: Edge Computing – EDGE 2019

Verlag: Springer International Publishing

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Abstract

Multicamera based Deep Learning vision applications subscribe to the Edge computing paradigm due to stringent latency requirements. However, guaranteeing latency in the wireless communication links between the cameras nodes and the Edge server is challenging, especially in the cheap and easily available unlicensed bands due to the interference from other camera nodes in the system, and from external sources. In this paper, we show how approximate computation techniques can be used to design a latency controller that uses multiple video frame image quality control knobs to simultaneously satisfy latency and accuracy requirements for machine vision applications involving object detection, and human pose estimation. Our experimental results on an Edge test bed indicate that the controller is able to correct for up to 164% degradation in latency due to interference within a settling time of under 1.15 s.

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Vorheriges Kapitel Characterization of IoT Workloads

Nächstes Kapitel Energy-Aware Capacity Provisioning and Resource Allocation in Edge Computing Systems

Mobilenet-ssd. https://github.com/chuanqi305/MobileNet-SSD. Accessed 12 Nov 2018

Opencv documentation. https://docs.opencv.org. Accessed 08 Nov 2018

Ben Khadra, M.A.: An introduction to approximate computing. CoRR abs/1711.06115 (2017). http://arxiv.org/abs/1711.06115

Betzel, F., Khatamifard, K., Suresh, H., Lilja, D.J., Sartori, J., Karpuzcu, U.: Approximate communication: techniques for reducing communication bottlenecks in large-scale parallel systems. ACM Comput. Surv. (CSUR) 51(1), 1 (2018)CrossRef

Bonomi, F., Milito, R., Natarajan, P., Zhu, J.: Fog computing: a platform for internet of things and analytics. In: Bessis, N., Dobre, C. (eds.) Big Data and Internet of Things: A Roadmap for Smart Environments. SCI, vol. 546, pp. 169–186. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-05029-4_7CrossRef

Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the internet of things. In: Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, MCC 2012, pp. 13–16. ACM, New York (2012). https://doi.org/10.1145/2342509.2342513

Cao, Z., Simon, T., Wei, S.E., Sheikh, Y.: Realtime multi-person 2D pose estimation using part affinity fields. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017). https://doi.org/10.1109/CVPR.2017.143

Chen, C., Choi, J., Gopalakrishnan, K., Srinivasan, V., Venkataramani, S.: Exploiting approximate computing for deep learning acceleration. In: 2018 Design, Automation & Test in Europe Conference & Exhibition, DATE 2018, Dresden, Germany, 19–23 March 2018, pp. 821–826 (2018). https://doi.org/10.23919/DATE.2018.8342119

Chiang, M., Zhang, T.: Fog and iot: an overview of research opportunities. IEEE Internet Things J. PP(99), 1 (2016)

10.

Ha, K., Chen, Z., Hu, W., Richter, W., Pillai, P., Satyanarayanan, M.: Towards wearable cognitive assistance. In: Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services, MobiSys 2014. pp. 68–81. ACM, New York, (2014). https://doi.org/10.1145/2594368.2594383

11.

Howard, A.G., et al.: Mobilenets: Efficient convolutional neural networks for mobile vision applications (2017)

12.

Ibrahim, A., Osta, M., Alameh, M., Saleh, M., Chible, H., Valle, M.: Approximate computing methods for embedded machine learning. In: 2018 25th IEEE International Conference on Electronics, Circuits and Systems (ICECS), pp. 845–848. IEEE (2018)

13.

Lecun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015)CrossRef

14.

Lee, E.A., et al.: The swarm at the edge of the cloud. IEEE Design Test 31(3), 8–20 (2014)CrossRef

15.

Liu, W., et al.: SSD: single shot multibox detector. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 21–37. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46448-0_2CrossRef

16.

Lu, Y., Chowdhery, A., Kandula, S.: Visflow: a relational platform for efficient large-scale video analytics. Technical report, June 2016. https://www.microsoft.com/en-us/research/publication/visflow-relational-platform-efficient-large-scale-video-analytics/

17.

Mittal, S.: A survey of techniques for approximate computing. ACM Comput. Surv. (CSUR) 48(4), 62 (2016)

18.

Pakha, C., Chowdhery, A., Jiang, J.: Reinventing video streaming for distributed vision analytics. In: 10th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 2018). USENIX Association, Boston, MA (2018). https://www.usenix.org/conference/hotcloud18/presentation/pakha

19.

Parag Shah, A., Lamare, J.B., Nguyen-Anh, T., Hauptmann, A.: CADP: a novel dataset for CCTV traffic camera based accident analysis, pp. 1–9 (2018)

20.

Rasouli, A., Kotseruba, I., Tsotsos, J.K.: Are they going to cross? A benchmark dataset and baseline for pedestrian crosswalk behavior. In: 2017 IEEE International Conference on Computer Vision Workshops (ICCVW), pp. 206–213 (2017)

21.

Sabella, D., Vaillant, A., Kuure, P., Rauschenbach, U., Giust, F.: Mobile-edge computing architecture: the role of mec in the internet of things. IEEE Consum. Electron. Mag. 5(4), 84–91 (2016)CrossRef

22.

Sapienza, M., Guardo, E., Cavallo, M., Torre, G.L., Leombruno, G., Tomarchio, O.: Solving critical events through mobile edge computing: an approach for smart cities. In: 2016 IEEE International Conference on Smart Computing (SMARTCOMP), pp. 1–5, May 2016

23.

Satyanarayanan, M., Bahl, P., Caceres, R., Davies, N.: The case for vm-based cloudlets in mobile computing. IEEE Pervasive Comput. 8(4), 14–23 (2009)CrossRef

24.

Shi, W., Cao, J., Zhang, Q., Li, Y., Xu, L.: Edge computing: vision and challenges. IEEE Internet Things J. 3(5), 637–646 (2016)CrossRef

25.

Vermesan, O., Friess, P., Guillemin, P., Gusmeroli, S.: Internet of Things Strategic Research Agenda. River Publishers, Alsbjergvej (2011)

26.

Zhang, W., Li, S., Liu, L., Jia, Z., Zhang, Y., Raychaudhuri, D.: Hetero-edge: orchestration of real-time vision applications on heterogeneous edge clouds (2019)

Titel: Latency Control for Distributed Machine Vision at the Edge Through Approximate Computing
verfasst von: Anjus George
Arun Ravindran
Verlag: Springer International Publishing
Buch: Edge Computing – EDGE 2019
Print ISBN: 978-3-030-23373-0

Electronic ISBN: 978-3-030-23374-7

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-23374-7_2

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