Abstract
The number of CCTV video surveillance systems has grown rapidly over the past decade. As CCTV systems are large energy consumers, the problem of optimising the energy consumption of CCTV systems is urgently needed. In this study, we analyse with mathematical models the energy balance consumption for an architecture that implements a path-by-learning prediction algorithm that predicts the path and destination of a mobile in a CCTV network in order to reduce energy consumption. This method significantly reduces the energy consumption of the CCTV system in real time. An experimental system is designed to evaluate the method and experiments are carried out to demonstrate the validity of the method. The experimental results show that the method has not only significantly improved resource use and reduced energy consumption.
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References
Song, M., Kim, M.: Solid state disk (SSD) management for reducing disk energy consumption in video servers. In: Proceedings of the 9th USENIX Conference on File and Storage Technologies, pp. 1–2 (2011)
Mohan Raj, V.K., Shriram, R.: Power aware provisioning in cloud computing environment. In: Proceedings of the International Conference on Communication and Electrical Technology (ICCCET), pp. 6–11. IEEE (2011)
Beaumont, O., Eyraud-Dubois, L., Thraves Caro, C., Rejeb, H.: Heterogeneous resource allocation under degree constraints. IEEE Trans. Parallel Distrib. Syst. 24(5), 926–37 (2013)
Hsu, W.H., Shieh, Y.P.: Virtual network mapping algorithm in the cloud infrastructure. J. Netw. Comput. Appl. 36(6), 1724–34 (2013)
Diop, P.S., Mbacke, A.B., Mendy, G.: Centralized and distributed architectures: approximation of the response time in a video surveillance system of road traffic by logarithm, power and linear functions. In: Puliafito, A., Bruneo, D., Distefano, S., Longo, F. (eds.) ADHOC-NOW 2017. LNCS, vol. 10517, pp. 314–327. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67910-5_26
Diop, P.S., Mbacké, A.B., Mendy, G.: Predictive assessment of response time for road traffic video surveillance systems: the case of centralized and distributed systems. In: Hsu, C.-H., Wang, S., Zhou, A., Shawkat, A. (eds.) IOV 2016. LNCS, vol. 10036, pp. 34–48. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-51969-2_4
Reyes, D.: Fully autonomous IEEE 802.3af Power over Ethernet midspan PSE requires no microcontroller, p. 576 (2016)
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Diop, P.S., Mbacké, A.B., Mendy, G., Gaye, I., Bilong, J.R.N. (2019). Optimisation of Energy Consumption in Traffic Video Monitoring Systems Using a Learning-Based Path Prediction Algorithm. In: Palattella, M., Scanzio, S., Coleri Ergen, S. (eds) Ad-Hoc, Mobile, and Wireless Networks. ADHOC-NOW 2019. Lecture Notes in Computer Science(), vol 11803. Springer, Cham. https://doi.org/10.1007/978-3-030-31831-4_26
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DOI: https://doi.org/10.1007/978-3-030-31831-4_26
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