Advertisement

Multimedia Tools and Applications

, Volume 78, Issue 5, pp 5523–5534 | Cite as

A study on the control of smart device set-top box using image based reverse mirroring technology

  • Hae-Jong Joo
  • Hwa-Young JeongEmail author
Article
  • 33 Downloads

Abstract

To measure the quality of service of IPTV, the quality of service (QoS) is measured at the front end of the subscriber’s STB. As is well known, QoS measures how reliably data are transmitted in a given network status. For example, the RTP packet header is scanned to analyze the packet loss, delay, jitter, etc. The IPTV services, however, send video data, including video and audio signals, and video data are sensitive to human sight and hearing. Back-mirroring technology is a function that enables the smart device to be utilized as a remote control device for interactive operation by wirelessly transmitting the screen of Android-based broadcasting devices (IPTV, smart TV, set-top box, etc.). In this paper, we suggest an advanced method and more diverse set of controls in order to process the signal from the set-top boxes or TV etc., suggesting that they are more convenient and more versatile. Using this solution, users will be able to use smart devices to increase user convenience and additional content markets by providing the same user convenience as smart devices, such as touch, drag, scaling, and scaling.

Keywords

Back Mirring Service quality of experience and service quality IPTV STB QoS QoE 

Notes

References

  1. 1.
    Cho D-g, Park S-c (2011) Design and implementation of quality measurement tools in wireless data services. KIIT 9(12):109–116 (8 pages)Google Scholar
  2. 2.
    Cho M-h, Park J-h, Yoo Y-i, Kim J-s, Kim S-j (2003) The study on the technology of measuring QoS for nespot. KICSGoogle Scholar
  3. 3.
    Cho M-T, Park D-S,Song H-B, Kim Y-C, Moon S-H (2012) Method and System for Measuring the Performance Based on the WIFI in Smart Media, EMC Technology and Service, LNEE 181, pp. 591–597.  https://doi.org/10.1007/978-94-007-5075-3_72
  4. 4.
    Dai Q, Lehnert R (2010) Impact of packet loss on the perceived video quality. IEEE INTERNETGoogle Scholar
  5. 5.
    Dunham MH, Kummer V (1999) Impact of mobility on transaction management. Proceeding of the international workshop on data engineering for wireless and mobile access, pp 14–21Google Scholar
  6. 6.
    Ekman C, Fouch JC, Sullivan ED Wireless network performance analysis system. the U.S. registered patent 2013-0279354Google Scholar
  7. 7.
    ITU-R R.ec. BT.500-11 (2002) Methodology for the subjective assessment of the quality of television pictures. ITU-RGoogle Scholar
  8. 8.
    ITU-T J.143 (2000) User requirements for objective perceptual video quality measurements in digital cable television series j: transmission of television, sound programme and other multimedia signals measurement of the quality of serviceGoogle Scholar
  9. 9.
    ITU-T Rec. P.910 (1999) Subjective video quality assessment methods for multimedia applications. ITU-TGoogle Scholar
  10. 10.
    Joo H-J, Jung H-Y (2017) Quality measurement system for a wireless network based on the multimedia-data service. Multimedia Tools and Applications 76(19):19795–19807CrossRefGoogle Scholar
  11. 11.
    Joo HJ, Park YB (2005) Design of reliable query processing system in mobile database environments. The KIPS Transactions Part D:521–530CrossRefGoogle Scholar
  12. 12.
    Joo H, Hong B, Kim S (2013) A study on smart traffic analysis and smart device speed measurement plaform. Lecture notes in electrical engineeringGoogle Scholar
  13. 13.
    Kim D (2011) Everything on the wireless network (WIFI). midasbook. Inc.Google Scholar
  14. 14.
    Kim H, Choi S (2010) A study on a QoS/QoE correlation model for QoE evaluation on IPTV service. IEEE ICACTGoogle Scholar
  15. 15.
    Lee J-h (2010) A study on communication service qualities of the three Mobile communication companies. e-business research 11(1)Google Scholar
  16. 16.
    Lee J-w (2011) Mapping: a study on maps for concept visualization. Design Research 24(4)Google Scholar
  17. 17.
    Liu Y, Nie L, Liu L, Rosenblum DS (2016) From action to activity: sensor-based activity recognition. Neurocomputing 181(12):108–115CrossRefGoogle Scholar
  18. 18.
    Maier G, Schneider F, Feldmann A (2010) A first look at Mobile hand-held device traffic. Passive and active measurement, Zurich, Switzerland, Apr. 7-9, pp 161–170CrossRefGoogle Scholar
  19. 19.
    Portokalidis G, Homburg P, Anagnostakis K, Bos H. Paranoid android: versatile protection for smartphones. Proceedings of the 26th Annual Computer Security Applications Conference, pp 347–356Google Scholar
  20. 20.
    Richardson T (1995) Teleporting—mobile X sessions. Proc. 9th Ann. X Technical Conf., Jan. 1995. Also in The X Resource, Issue 13, O’Reilly & Associates, Jan. Also available as ORL Technical Report 95.5, ORL, Cambridge CB2 1QA, EnglandGoogle Scholar
  21. 21.
    Richardson T et al (1994) Teleporting in an X window system environment. IEEE Pers Commun 1(3):6–12. Also available as ORL Technical Report 94.4, ORL, Cambridge CB2 1QA, EnglandCrossRefGoogle Scholar
  22. 22.
    Richardson T, Stafford-Fraser Q, Wood KR, Hoper A (1998) Virtual network computing. IEEE Internet Comput 2(1):33–38CrossRefGoogle Scholar
  23. 23.
    Shabtai A, Fledel Y, Kanonov U, Elovici Y, Dolev S (2009) A state-of-the-art review of security mechanisms. Cornell UniversityGoogle Scholar
  24. 24.
    Shumeli R, Hadar O, Huber R, Maltz M, Huber M (2008) Effects of an encoding scheme on perceived video quality transmitted over lossy internet protocol networks. IEEE Trans Broadcast 54(3):628–640CrossRefGoogle Scholar
  25. 25.
    Wood KR et al (1997) Global teleporting with Java: toward ubiquitous personalized computing. Computer 30(2):53–59. Also available as ORL technical report 96.2, ORL, Cambridge CB2 1QA, EnglandCrossRefGoogle Scholar
  26. 26.
    Yoon T-L, Cynn H-S, Choi S-A, Choi W-J, Lee J-H, Choi B-S (2015) Visual feedback using a smart-phone mirroring system influences trunk muscle activity and kinematics of the trunk and pelvis in healthy and chronic low-back pain groups during arm and leg lift in quadruped position. Isokinet Exerc Sci 23(2):117–125CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer Science & EngineeringDongguk UniversitySeoulSouth Korea
  2. 2.Departmet of Humanitas CollegeKyung Hee UniversitySeoulSouth Korea

Personalised recommendations