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QoE Analysis of Real-Time Video Streaming over 4G-LTE for UAV-Based Surveillance Applications

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Intelligent Technologies and Applications (INTAP 2019)

Abstract

Drones also known as Unmanned Aerial Vehicles (UAVs) perform an significant role in surveillance at a remote location by streaming real-time video with their attached cameras. A good architecture for such kind of surveillance is required that ensures real-time monitoring at targeted areas. As the streaming video is used in monitoring; it is much important to ensure its quality during transmission so that remote client can view clear insights and could take prompt action on time if required. In this paper, we have proposed a 4G-LTE architecture and examined the effects of different factors in such architecture. We have shown the comparative analysis between two latest codec schemes i.e. H.264 and H.265 (HEVC) in video streaming. Our study is an important step towards exploring the factors that influence the real-time video streaming and degrade the Quality of Experience (QoE) of video viewing in such architecture. To examine the received video quality, two objective metrics, Peak-Signal-to-Noise-Ratio (PSNR) and Structural-Similarity-Index (SSIM) have been considered in this paper. The simulation results are based on the most famous Network simulator in the research community i.e. NS-3. The results have shown that H.265 works better in comparison with H.264 under different circumstances.

Supported by PAF-Karachi Institute of Economics and Technology Karachi.

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References

  1. EvalVid Binaries for Calculation of PSNR and SSIM. http://www2.tkn.tu-berlin.de/research/evalvid/fw.html

  2. FFmpeg. https://ffmpeg.org/

  3. GERCOM. http://www.gercom.ufpa.br

  4. MP4Box. https://gpac.wp.imt.fr/mp4box/

  5. PSNR and SSIM Computation. http://totalgeekout.blogspot.com/2013/04/evalvid-on-ns-3-on-ubuntu-1204.html

  6. DIGI Application Note, June 2012. http://ftp1.digi.com/support/images/XST-AN005a-IndoorPathLoss.pdf

  7. Alsmirat, M.A., Jararweh, Y., Obaidat, I., Gupta, B.B.: Automated wireless video surveillance: an evaluation framework. J. Real-Time Image Process. 13(3), 527–546 (2017). https://doi.org/10.1007/s11554-016-0631-x

    Article  Google Scholar 

  8. Amirpour, H., Pinheiro, A.M., Pereira, M., Ghanbari, M.: Reliability of the most common objective metrics for light field quality assessment. In: ICASSP 2019–2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2402–2406. IEEE (2019)

    Google Scholar 

  9. Angelov, P., Sadeghi-Tehran, P., Clarke, C.: AURORA: autonomous real-time on-board video analytics. Neural Comput. Appl. 28(5), 855–865 (2017). https://doi.org/10.1007/s00521-016-2315-7

    Article  Google Scholar 

  10. Avcibaş, I., Sankur, B., Sayood, K.: Statistical evaluation of image quality measures. J. Electron. Imaging 11(2), 206–223 (2002)

    Article  Google Scholar 

  11. Bekmezci, I., Sahingoz, O.K., Temel, Ş.: Flying ad-hoc networks (FANETs): a survey. Ad Hoc Netw. 11(3), 1254–1270 (2013)

    Article  Google Scholar 

  12. Cadik, M., Slavik, P.: Evaluation of two principal approaches to objective image quality assessment. In: Proceedings of the Eighth International Conference on Information Visualisation, IV 2004, pp. 513–518. IEEE (2004)

    Google Scholar 

  13. Challita, U., Ferdowsi, A., Chen, M., Saad, W.: Artificial intelligence for wireless connectivity and security of cellular-connected UAVs. arXiv preprint arXiv:1804.05348 (2018)

  14. Channappayya, S.S., Bovik, A.C., Heath, R.W.: A linear estimator optimized for the structural similarity index and its application to image denoising, October 2006

    Google Scholar 

  15. Dosselmann, R., Yang, X.D.: Existing and emerging image quality metrics. In: Canadian Conference on Electrical and Computer Engineering, pp. 1906–1913. IEEE (2005)

    Google Scholar 

  16. Hamida, A.B., Koubaa, M., Nicolas, H., Amar, C.B.: Video surveillance system based on a scalable application-oriented architecture. Multimed. Tools Appl. 75(24), 17187–17213 (2016). https://doi.org/10.1007/s11042-015-2987-5

    Article  Google Scholar 

  17. Hore, A., Ziou, D.: Image quality metrics: PSNR vs. SSIM. In: 2010 20th International Conference on Pattern Recognition, pp. 2366–2369. IEEE (2010)

    Google Scholar 

  18. Huynh-Thu, Q., Ghanbari, M.: Scope of validity of PSNR in image/video quality assessment. Electron. Lett. 44(13), 800 (2008)

    Article  Google Scholar 

  19. Ivancic, W.D., Kerczewski, R.J., Murawski, R.W., Matheou, K., Downey, A.N.: Flying drones beyond visual line of sight using 4G LTE: issues and concerns. In: 2019 Integrated Communications, Navigation and Surveillance Conference (ICNS), pp. 1–13. IEEE (2019)

    Google Scholar 

  20. Jiang, X., Feng, J., Song, T., Katayama, T.: Low-complexity and hardware-friendly H.265/HEVC encoder for vehicular ad-hoc networks. Sensors 19(8), 1927 (2019)

    Article  Google Scholar 

  21. Jung, J., Yoo, S., La, W., Lee, D., Bae, M., Kim, H.: AVSS: airborne video surveillance system. Sensors 18(6), 1939 (2018)

    Article  Google Scholar 

  22. Jung, S., Jo, Y., Kim, Y.J.: Aerial surveillance with low-altitude long-endurance tethered multirotor UAVs using photovoltaic power management system. Energies 12(7), 1323 (2019)

    Article  Google Scholar 

  23. Karaki, H.S.A., Alomari, S.A., Refai, M.H.: A comprehensive survey of the vehicle motion detection and tracking methods for aerial surveillance videos. IJCSNS 19(1), 93 (2019)

    Google Scholar 

  24. Kim, H., Ben-Othman, J.: A collision-free surveillance system using smart UAVs in multi domain IoT. IEEE Commun. Lett. 22(12), 2587–2590 (2018)

    Article  Google Scholar 

  25. Korhonen, J., You, J.: Improving objective video quality assessment with content analysis. In: Proceedings of the International Workshop on Video Processing and Quality Metrics for Consumer Electronics, pp. 1–6 (2010)

    Google Scholar 

  26. Kwak, J., Park, J.H., Sung, Y.: Emerging ICT UAV applications and services: design of surveillance UAVs. Int. J. Commun. Syst. e4023 (2019)

    Google Scholar 

  27. Lee, S., et al.: Design and development of a DDDAMS-based border surveillance system via UVs and hybrid simulations. Expert Syst. Appl. 128, 109–123 (2019)

    Article  Google Scholar 

  28. Lei, X., Jiang, X., Wang, C.: Design and implementation of a real-time video stream analysis system based on FFmpeg. In: 2013 Fourth World Congress on Software Engineering, pp. 212–216. IEEE (2013)

    Google Scholar 

  29. Li, S., Ngan, K.N.: Influence of the smooth region on the structural similarity index. In: Muneesawang, P., Wu, F., Kumazawa, I., Roeksabutr, A., Liao, M., Tang, X. (eds.) PCM 2009. LNCS, vol. 5879, pp. 836–846. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-10467-1_74

    Chapter  Google Scholar 

  30. Lyon, D.: The Electronic Eye: The Rise of Surveillance Society. University of Minnesota Press, Minneapolis (1994)

    Google Scholar 

  31. MacKenzie, D., Wajcman, J.: The Social Shaping of Technology. Open University Press, London (1999)

    Google Scholar 

  32. Marwat, S.N.K., Meyer, S., Weerawardane, T., Goerg, C.: Congestion-aware handover in LTE systems for load balancing in transport network. ETRI J. 36(5), 761–771 (2014)

    Article  Google Scholar 

  33. Medda, A., DeBrunner, V.: Color image quality index based on the UIQI. In: 2006 IEEE Southwest Symposium on Image Analysis and Interpretation, pp. 213–217. IEEE (2006)

    Google Scholar 

  34. Mengzhe, L., Xiuhua, J., Xiaohua, L.: Analysis of H.265/HEVC, H.264 and VP9 coding efficiency based on video content complexity. In: 2015 IEEE International Conference on Computer and Communications (ICCC), pp. 420–424. IEEE (2015)

    Google Scholar 

  35. Motlagh, N.H., Bagaa, M., Taleb, T.: UAV-based IoT platform: a crowd surveillance use case. IEEE Commun. Mag. 55(2), 128–134 (2017)

    Article  Google Scholar 

  36. Motlagh, N.H., Bagaa, M., Taleb, T., Song, J.: Connection steering mechanism between mobile networks for reliable UAV’s IoT platform. In: 2017 IEEE International Conference on Communications (ICC), pp. 1–6. IEEE (2017)

    Google Scholar 

  37. Mukherjee, A., Keshary, V., Pandya, K., Dey, N., Satapathy, S.C.: Flying ad hoc networks: a comprehensive survey. In: Satapathy, S.C., Tavares, J.M.R.S., Bhateja, V., Mohanty, J.R. (eds.) Information and Decision Sciences. AISC, vol. 701, pp. 569–580. Springer, Singapore (2018). https://doi.org/10.1007/978-981-10-7563-6_59

    Chapter  Google Scholar 

  38. Mustaqim, M., Khawaja, B.A., Razzaqi, A.A., Zaidi, S.S.H., Jawed, S.A., Qazi, S.H.: Wideband and high gain antenna arrays for UAV-to-UAV and UAV-to-ground communication in flying ad-hoc networks (FANETs). Microwave Opt. Technol. Lett. 60(5), 1164–1170 (2018)

    Article  Google Scholar 

  39. Najiya, K., Archana, M.: UAV video processing for traffic surveillence with enhanced vehicle detection. In: 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), pp. 662–668. IEEE (2018)

    Google Scholar 

  40. Nguyen, T.B., Ziou, D.: Contextual and non-contextual performance evaluation of edge detectors. Pattern Recogn. Lett. 21(9), 805–816 (2000)

    Article  Google Scholar 

  41. Park, J.H., Choi, S.C., Ahn, I.Y., Kim, J.: Multiple UAVs-based surveillance and reconnaissance system utilizing IoT platform. In: 2019 International Conference on Electronics, Information, and Communication (ICEIC), pp. 1–3. IEEE (2019)

    Google Scholar 

  42. Qazi, S., Alvi, A., Qureshi, A.M., Khawaja, B.A., Mustaqim, M.: An architecture for real time monitoring aerial adhoc network. In: 2015 13th International Conference on Frontiers of Information Technology (FIT), pp. 154–159. IEEE (2015)

    Google Scholar 

  43. Qazi, S., Siddiqui, A.S., Wagan, A.I.: UAV based real time video surveillance over 4G LTE. In: 2015 International Conference on Open Source Systems & Technologies (ICOSST), pp. 141–145. IEEE (2015)

    Google Scholar 

  44. Sarkar, S., Totaro, M.W., Elgazzar, K.: Intelligent drone-based surveillance: application to parking lot monitoring and detection. In: Unmanned Systems Technology XXI, vol. 11021, p. 1102104. International Society for Optics and Photonics (2019)

    Google Scholar 

  45. Semsch, E., Jakob, M., Pavlicek, D., Pechoucek, M.: Autonomous UAV surveillance in complex urban environments. In: Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology-Volume 02, pp. 82–85. IEEE Computer Society (2009)

    Google Scholar 

  46. Seshadrinathan, K., Soundararajan, R., Bovik, A.C., Cormack, L.K.: Study of subjective and objective quality assessment of video. IEEE Trans. Image Process. 19(6), 1427–1441 (2010)

    Article  MathSciNet  Google Scholar 

  47. Sharma, V., Song, F., You, I., Chao, H.C.: Efficient management and fast handovers in software defined wireless networks using UAVs. IEEE Netw. 31(6), 78–85 (2017)

    Article  Google Scholar 

  48. Sheikh, H.R., Bovik, A.C., De Veciana, G.: An information fidelity criterion for image quality assessment using natural scene statistics. IEEE Trans. Image Process. 14(12), 2117–2128 (2005)

    Article  Google Scholar 

  49. Shin, S.Y., et al.: UAV based search and rescue with honeybee flight behavior in forest. In: Proceedings of the 5th International Conference on Mechatronics and Robotics Engineering, pp. 182–187. ACM (2019)

    Google Scholar 

  50. Vijaykumar, M., Rao, S.: A cross-layer frame work for adaptive video streaming over wireless networks, September 2010

    Google Scholar 

  51. Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P., et al.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)

    Article  Google Scholar 

  52. Yan, B., Bare, B., Ma, C., Li, K., Tan, W.: Deep objective quality assessment driven single image super-resolution. IEEE Trans. Multimed. 21, 2957–2971 (2019)

    Article  Google Scholar 

  53. Yang, K., Gong, Y., Ma, M., Wu, H.R.: An efficient rate-distortion optimization method for low-delay configuration in H.265/HEVC based on temporal layer rate and distortion dependency. IEEE Trans. Circuits Syst. Video Technol. 29, 1230–1236 (2019)

    Article  Google Scholar 

  54. Yang, T., Li, Z., Zhang, F., Xie, B., Li, J., Liu, L.: Panoramic UAV surveillance and recycling system based on structure-free camera array. IEEE Access 7, 25763–25778 (2019)

    Article  Google Scholar 

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Naveed, M., Qazi, S. (2020). QoE Analysis of Real-Time Video Streaming over 4G-LTE for UAV-Based Surveillance Applications. In: Bajwa, I., Sibalija, T., Jawawi, D. (eds) Intelligent Technologies and Applications. INTAP 2019. Communications in Computer and Information Science, vol 1198. Springer, Singapore. https://doi.org/10.1007/978-981-15-5232-8_38

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  • DOI: https://doi.org/10.1007/978-981-15-5232-8_38

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