A Review of Satellite Video on Demand with Evolutionary Computing

  • De Yao Lin
  • Xuehong HuangEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 834)


As technology has developed, satellite TV has played an increasingly important role in the national economic construction. It has repeatedly provided outstanding services in situations such as earthquake relief, border posts, and foreign hotels by maintaining communication with the outside. Although technological progress has led to the development of both digital and analogue satellite TV, the former is much more expensive than the latter. Hence, there is likely to be some waste on some occasions if digital satellite TV is always chosen. This paper focuses on the technical characteristics of simulation and digital satellite TV, guiding people to adopt different design schemes for different situations, so as to maximize the benefits of satellite TV while having limited funds. This study also briefly analyzed the entire process of satellite TV design, installation, and debugging from a technical point of view to ensure that people can safely enjoy satellite TV. This paper also investigates the research in satellite video on demand and provides a review of applied evolutionary computing that improve video-on-demand service.


Satellite TV Safe grounding Video on demand Evolutionary computing 


  1. 1.
    Yao, Y.Y., et al.: Development Trend of Broadcast TV and Business Bundling Technology. Radio & TV Information, 03 (2010)Google Scholar
  2. 2.
    Kang, Y.: Development and Challenges of Gansu Broadcast TV Digital Service. Cable TV Technology, 11 (2006)Google Scholar
  3. 3.
    Zhong, X.D.: Analysis on the Development of Digital TV in China. China Media Technology, 02 (2013)Google Scholar
  4. 4.
    He, Y., Lee, I., Guan, L.: Distributed throughput maximization in P2P VoD applications. IEEE Trans. Multimed. (TMM) 11(3), 509–522 (2009)CrossRefGoogle Scholar
  5. 5.
    Lee, I., He, Y., Guan, L.: Centralized P2P streaming with MDC. In: Proceedings of Multimedia Signal Processing Workshop (MMSP), Shanghai, China, October (2005)Google Scholar
  6. 6.
    Cominetti, M., Morello, A.: Digital video broadcasting over satellite (DVB-S): a system for broadcasting and contribution applications. Int. J. Satell. Commun. 18(6), 393–410 (2000)CrossRefGoogle Scholar
  7. 7.
    Le-Ngoc, T., Tsingotjidis, P.: Provision of video-on-demand services via broadband GEO satellite systems. In: Mobile and Personal Satellite Communications 3, pp. 222–234 (1999)Google Scholar
  8. 8.
    Yang, T., et al.: Small moving vehicle detection in a satellite video of an urban area. Sensors 16(9), 1528 (2016)CrossRefGoogle Scholar
  9. 9.
    Pradas, D., Vazquez-Castro, M.A.: NUM-based fair rate-delay balancing for layered video multicasting over adaptive satellite networks. IEEE J. Sel. Areas Commun. 29(5), 969–978 (2011)CrossRefGoogle Scholar
  10. 10.
    Ma, T., Lee, Y.H., Winkler, S., Ma, M.: QoS provisioning by power control for video communication via satellite links. Int. J. Satell. Commun. Network. 33(3), 259–275 (2015)CrossRefGoogle Scholar
  11. 11.
    Imole, O.E., Walingo, T.: Call admission control for rain-impacted multimedia satellite networks. In: 2017 IEEE AFRICON, pp. 371–376 (2017)Google Scholar
  12. 12.
    Lee, Y.H., Winkler, S.: Effects of rain attenuation on satellite video transmission. In: 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring), pp. 1–5 (2011)Google Scholar
  13. 13.
    Eiben, A.E., Smith, J.: From evolutionary computation to the evolution of things. Nature 521(7553), 476–482 (2015)CrossRefGoogle Scholar
  14. 14.
    Cheng, P., Lee, I., Lin, C.W., Pan, J.S.: Association rule hiding based on evolutionary multi-objective optimization. Intell. Data Anal. 20(3), 495–514 (2016)CrossRefGoogle Scholar
  15. 15.
    Mansour, R.F.: Evolutionary computing enriched computer-aided diagnosis system for diabetic retinopathy: a survey. IEEE Rev. Biomed. Eng. 10, 334–349 (2017)CrossRefGoogle Scholar
  16. 16.
    Merkle, D., Middendorf, M., Schmeck, H.: Ant colony optimization for resource-constrained project scheduling. IEEE Trans. Evol. Comput. 6(4), 333–346 (2002)CrossRefGoogle Scholar
  17. 17.
    Marzband, M., Yousefnejad, E., Sumper, A., Domínguez-García, J.L.: Real time experimental implementation of optimum energy management system in standalone microgrid by using multi-layer ant colony optimization. Int. J. Electr. Power Energy Syst. 75, 265–274 (2016)CrossRefGoogle Scholar
  18. 18.
    De Rango, F., Tropea, M., Santamaria, A.F., Marano, S.: An enhanced QoS CBT multicast routing protocol based on Genetic Algorithm in a hybrid HAP–Satellite system. Comput. Commun. 30(16), 3126–3143 (2007)CrossRefGoogle Scholar
  19. 19.
    Rango, F.D., Tropea, M., Santamaria, A.F., Marano, S.: Multicast QoS core-based tree routing protocol and genetic algorithm over an HAP-satellite architecture. IEEE Trans. Veh. Technol. 58(8), 4447–4461 (2009)CrossRefGoogle Scholar
  20. 20.
    Xu, C., Jia, S., Zhong, L., Zhang, H., Muntean, G.: Ant-inspired mini-community-based solution for video-on-demand services in wireless mobile networks. IEEE Trans. Broadcast. 60(2), 322–335 (2014)CrossRefGoogle Scholar
  21. 21.
    Huang, R., Tawfik, H., Nagar, A.: Electronic fraud detection for video-on-demand system using hybrid immunology-inspired algorithms. In: Artificial Immune Systems, pp. 290–303 (2010)Google Scholar
  22. 22.
    Tang, K.S., Ko, K.T., Chan, S., Wong, E.: Video placement in video-on-demand system using genetic algorithm. In: Proceedings of IEEE International Conference on Industrial Technology, pp. 672–676 (2000)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.National Demonstration Center for Experimental Electronic Information and Electrical Technology EducationFujian University of TechnologyFuzhouChina

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