Multimedia Tools and Applications

, Volume 75, Issue 21, pp 13333–13348 | Cite as

QoS-adaptive service configuration framework for cloud-assisted video surveillance systems

  • Atif Alamri
  • M. Shamim Hossain
  • Ahmad Almogren
  • Mohammad Mehedi Hassan
  • Khalid Alnafjan
  • Mohammed Zakariah
  • Lee Seyam
  • Abdullah Alghamdi
Article
First Online:
Received:
Revised:
Accepted:

Abstract

Quality of service (QoS)-adaptive service configuration is crucial for seamless access to video services in cloud-assisted video surveillance systems. To maintain seamless access to video on a user’s preferred device, suitable video transcoding services are needed. It is a challenging task to choose and configure these services for various devices to ensure QoS-adaptive user experiences. To configure these services for the desired user devices, a suitable configuration algorithm is needed. Therefore, this paper describes a QoS-adaptive service configuration approach to choose the optimal configuration for the preferred user devices in varied contexts so that the user can access the services ubiquitously. We implemented a cloud-assisted video surveillance prototype to show how the proposed method can handle ubiquitous access to target video for possible QoS-adaptive and video processing requirements in terms of bandwidth, delay, and frame rates. The results show that the proposed configuration method outperforms the other comparable approaches.

Keywords

Adaptive QoS Cloud-assisted video surveillance Service configuration Transcoding service 

Notes

Acknowledgments

This project was full financially supported by the King Saud University, through Vice Deanship of Research Chairs.

References

  1. 1.
    Ahmed DT, Hossain MA, Shirmohammadi S, Ghamdi AA, Atrey PK, El Saddik A (2014) Utility based decision support engine for camera view selection in multimedia surveillance systems. Multimed Tools Applic 73(1):219–240CrossRefGoogle Scholar
  2. 2.
    Axis, “Video surveillance as a service (VsaaS),” http://www.axis.com/products/video/about networkvideo/vsaas.htm. Accessed March 2015
  3. 3.
    Cui X, Lin C, Wei Y (2003) A multiobjective model for QoS multicast routing based on genetic algorithm. In: Proceedings of the , ICCNMC’03, Shanghai, China, 20–23 Oct 2003Google Scholar
  4. 4.
    Ejaz N, Tariq TB, Baik SW (2012) Adaptive key frame extraction for video summarization using an aggregation mechanism. J Vis Commun Image Represent 23(7):1031–1040CrossRefGoogle Scholar
  5. 5.
    Hassan MM, Hossain MA, Abdullah-Al-Wadud M, Al-Mudaihesh T, Alyahya S, Ghamdi AA. (2015) A scalable and elastic cloud-assisted publish/subscribe model for IPTV video surveillance system. Cluster Computing, Springer 1–10Google Scholar
  6. 6.
    Hassan MM, Hossain MA, Al-Qurishi M (2014) Cloud-based mobile IPTV terminal for video surveillance. In: Proceedings of the 16th IEEE ICACT '14 876–880, South Korea, 16–19 Feb 2014Google Scholar
  7. 7.
    Hossain MA (2013) Analyzing the suitability of cloud-based multimedia surveillance systems. In: Proceedings of the HPCC_EUC’13, Porto, Portugal, 21–23 Oct 2013Google Scholar
  8. 8.
    Hossain MS (2014) QoS-based service composition for distributed video surveillance. Multimed Tools Applic 73(1):169–188CrossRefGoogle Scholar
  9. 9.
    Hossain MA (2014) Framework for a cloud-based multimedia surveillance system. International Journal of Distributed Sensor Networks 2014Google Scholar
  10. 10.
    Hossain MS, Alamri A, El Saddik A (2009) A biologically-inspired framework for multimedia service management in ubiquitous environment. Concurr Comput Pract Experien 21(11):1450–1466CrossRefGoogle Scholar
  11. 11.
    Hossain MS, El Saddik A (2006) Scalability measurement of a proxy based personalized multimedia repurposing system. In:Proceedings of the IEEE IMTC’06, Sorrento, Italy, 24–27 Apr 2006Google Scholar
  12. 12.
    Hossain MS, El Saddik A (2010) QoS requirement in the multimedia transcoding service selection process. IEEE Trans Instrum Meas 59(6):1498–1506CrossRefGoogle Scholar
  13. 13.
    Hossain MS, Hassan MM (2013) An hybrid ACO-based approach for media service composition in video surveillance platform. In: Proceeding of the IEEE, ICME’13, San Jose, California, USA, 15–19 July 2013Google Scholar
  14. 14.
    Hossain MS, Hassan MM, Qurishi MA, and Ghamdi AA (2012) Resource allocation for service composition in cloud-based video surveillance platform. In: Proceedings of the IEEE Multimedia and Expo Workshops ICMEW’12, Melbourne, Australia, 09-13 Jul 2012Google Scholar
  15. 15.
    Hossain MS, Hossain SA, Alamri A, Hossain MA (2013) Ant-based service selection framework for a smart home monitoring environment. Multimed Tools Applic 67(2):433–453CrossRefGoogle Scholar
  16. 16.
    Iqbal R, Ratti S, Shirmohammadi S (2009) A distributed camera network architecture supporting video adaptation. In: Proceedings of the ACM/IEEE ICDSC’09, Montreal, Québec, Canada, 30 Aug-2 Sep 2009Google Scholar
  17. 17.
    Lamy-Bergot C, Renan E, Gadat B, Lavaux D (2009) Data supervision for adaptively transcoded video surveillance over wireless links. In: Proceedings of the IEEE ITST'09, Lille, France, 20-22 Oct. 2009, pp. 415-419Google Scholar
  18. 18.
    Limna T, and Tandayya P (2012) Design for a flexible video surveillance as a service. In: Proceedings of the  IEEE CISP’ 12, Sichuan, China, 16-18 Oct 2012Google Scholar
  19. 19.
    Musunoori S, Horn G (2006) Ant-based approach to the quality aware application service partitioning in a gridenvironment. In: Proceedings of the IEEE CEC’06,Vancouver, Canada, 16–21 July ‘06, pp. 2604–2611Google Scholar
  20. 20.
    Qi L, Dou W, Zhang X, Chen J (2012) A QoS-aware composition method supporting cross-platform service invocation in cloud environment. J Comput Syst Sci 78(5):1316–1329CrossRefMATHGoogle Scholar
  21. 21.
    Rodriguez-Silva D, Adkinson-Orellana L, Gonz'lez-Castano FJ, Gonz'lez-Martinez D (2012) Video surveillance based on cloud storage. In. 5th International Conference on Cloud Computing CLOUD’12, Hyatt Regency Waikiki Resort and Spa, Honolulu, Hawaii, USAGoogle Scholar
  22. 22.
    Shanshan Z, Lei W, Lin M, Zepeng W (2012) An improved ant colony optimization algorithm for QoS-aware dynamic web service composition. In: Proceedings of the ICICEE’12, Xi’an, China, 23–25 Aug 2012Google Scholar
  23. 23.
    Song B, Hassan MM, Tian Y, Hossain MS, Alamri A. (2015) Remote display solution for video surveillance in multimedia cloud. Multimed Tools Applic 2015Google Scholar
  24. 24.
    Song B, Tian Y, Zhou B (2014) Design and evaluation of remote video surveillance system on private cloud. In: Proceedings of the IEEE ISBAST’14, Kuala Lumpur, Malaysia, 26–27 Aug 2014Google Scholar
  25. 25.
    Wang Z, Liu S, Fan Q (2013) Cloud-based platform for embedded wireless video surveillance system. In: Proceedings of the IEEE ICCIS’13, Shiyan, Hubei, China, 21–23 June 2013Google Scholar
  26. 26.
    Xu D, Wichadakul D, Nahrstedt K (2000) Multimedia service configuration and reservation in heterogeneous environments. In: Proceedings of the IEEE DCS’00, Istanbul, Turkey, 05–09 June 2000Google Scholar
  27. 27.
    Yang Z, Shang C, Liu Q, Zhao C (2010) A dynamic web services composition algorithm based on the combination of ant colony algorithm and genetic algorithm. J Comput Inform Syst 6(8):2617–2622Google Scholar
  28. 28.
    Ye Z, Zhou X, Bouguettaya A (2011) Genetic algorithm based QoS-aware service compositions in cloud computing. Database systems for advanced applications, Volume 6588 of the series Lecture Notes in Computer Science 321–334Google Scholar
  29. 29.
    Zeng C, Guo X, Ou W, Han D (2009) Cloud computing service composition and search based on semantic. Cloud Comput 290–300Google Scholar
  30. 30.
    Zou G, Chen Y, Yang Y, Huang R, and Xu Y (2010) AI planning and combinatorial optimization for web service composition in cloud computing. In: Proceedings of the CCV’2010 Singapore, 17–18 May 2010Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Atif Alamri
    • 1
  • M. Shamim Hossain
    • 1
    • 2
  • Ahmad Almogren
    • 1
  • Mohammad Mehedi Hassan
    • 1
  • Khalid Alnafjan
    • 2
  • Mohammed Zakariah
    • 1
  • Lee Seyam
    • 3
  • Abdullah Alghamdi
    • 2
  1. 1.Research Chair of Pervasive and Mobile Computing, College of Computer and Information Sciences (CCIS)King Saud UniversityRiyadhSaudi Arabia
  2. 2.SwE Department, College of Computer and Information Sciences (CCIS)King Saud UniversityRiyadhSaudi Arabia
  3. 3.Department of Electrical EngineeringKyung Hee UniversityDongdaemunKorea

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