Abstract
Surveillance video data are characterized by a high-volume write-oriented workload and cyclic use of storage space at full capacity. Besides, the video data needs indexing to support accurate-query. Data archiving for such applications, however, is complicated by the increasing demands of higher-resolution cameras and longer video-retention times. Due to the constant data steaming and nearly 100% write activity, general-purpose file systems will not suffice for present purposes. Thus, we specially design and implement a lightweight video storage file system (LVFS) for IP camera-based surveillance applications. LVFS provides a recycled storage platform to meet the retention requirement of surveillance applications, and delivers high performance for concurrent stream data uploading from multiple cameras and accurate data retrieval. Results of a multi-workload experiment show that LVFS is able to archive 40 HD or 16 full-HD cameras for an individual hard disk while processing nearly constant time queries, indicating that LVFS successfully fits the system requirement and performs better than general-purpose file system.
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References
Bramberger, M., Doblander, A., Maier, A., Rinner, B., Schwabach, H.: Distributed embedded smart cameras for surveillance applications. computer 39(2), 68–75 (2006)
Chang, R.I., Wang, T.C., Wang, C.H., Liu, J.C., Ho, J.M.: Effective distributed service architecture for ubiquitous video surveillance. Inf. Syst. Front. 14(3), 499–515 (2012)
Chen, X., Zhang, C.: A spatio-temporal database model on transportation surveillance videos. In: Proceedings of the Third Workshop on Spatio-Temporal Database Management STDBM 2006, p. 17 (2006)
Desnoyers, P., Shenoy, P.J.: Hyperion: high volume stream archival for retrospective querying. In: USENIX Annual Technical Conference, pp. 45–58 (2007)
Diallo, O., Rodrigues, J.J., Sene, M.: Real-time data management on wireless sensor networks: a survey. J. Netw. Comput. Appl. 35(3), 1013–1021 (2012)
Hossain, M.A.: Analyzing the suitability of cloud-based multimedia surveillance systems. In: 2013 IEEE 10th International Conference on High Performance Computing and Communications and 2013 IEEE International Conference on Embedded and Ubiquitous Computing (HPCC_EUC), pp. 644–650. IEEE (2013)
Hossain, M.A.: Framework for a cloud-based multimedia surveillance system. Int. J. Distrib. Sens. Netw. 10(5), 135257 (2014)
Hossain, M.S., Hassan, M.M., Al Qurishi, M., Alghamdi, A.: Resource allocation for service composition in cloud-based video surveillance platform. In: 2012 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), pp. 408–412. IEEE (2012)
Huang, T.: Surveillance video: the biggest big data. Comput. Now 7(2), 82–91 (2014)
Layton, J.B.: Nilfs: a file system to make SSDs scream. Linux Mag., 6 (2009)
Li, S., Liu, W., Ma, H., Fu, H.: Multi-attribute based fire detection in diverse surveillance videos. In: Amsaleg, L., Guðmundsson, G.Þ., Gurrin, C., Jónsson, B.Þ., Satoh, S. (eds.) MMM 2017. LNCS, vol. 10132, pp. 238–250. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-51811-4_20
Limna, T., Tandayya, P.: A flexible and scalable component-based system architecture for video surveillance as a service, running on infrastructure as a service. Multimedia Tools Appl. 75(4), 1765–1791 (2016)
Liu, H., Chen, S., Kubota, N.: Intelligent video systems and analytics: a survey. IEEE Trans. Ind. Inf. 9(3), 1222–1233 (2013)
Lo, W.T., Chang, Y.S., Sheu, R.K., Yang, C.T., Juang, T.Y., Wu, Y.S.: Implementation and evaluation of large-scale video surveillance system based on P2P architecture and cloud computing. Int. J. Distrib. Sens. Netw. 10(4), 375871 (2014)
Piroska, H., Gyula, F., Ioan-Cosmin, S.: Data storage for smart environment using non-SQL databases. In: 2012 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 305–308. IEEE (2012)
Räty, T.D.: Survey on contemporary remote surveillance systems for public safety. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 40(5), 493–515 (2010)
Ye, G., Liao, W., Dong, J., Zeng, D., Zhong, H.: A surveillance video index and browsing system based on object flags and video synopsis. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds.) MMM 2015. LNCS, vol. 8936, pp. 311–314. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-14442-9_36
Zhizhuo, S., Yu-An, T., Yuanzhang, L.: An energy-efficient storage for video surveillance. Multimedia Tools Appl. 73(1), 151–167 (2014)
Acknowledgment
Firstly, we would like to thank the reviewers for the careful and thorough reading of our manuscript and for the insightful comments and constructive suggestions. Secondly, this work is supported in part by the National Basic Research Program (973 Program) of China under Grant No. 2011CB302305, the National Natural Science Foundation of China under Grant No. 61232004. NSF-CNS-1116606.
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Wang, C., Zhou, K., Niu, Z., Wei, R., Li, H. (2018). LVFS: A Lightweight Video Storage File System for IP Camera-Based Surveillance Applications. In: Schoeffmann, K., et al. MultiMedia Modeling. MMM 2018. Lecture Notes in Computer Science(), vol 10705. Springer, Cham. https://doi.org/10.1007/978-3-319-73600-6_17
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DOI: https://doi.org/10.1007/978-3-319-73600-6_17
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