Skip to main content
SpringerLink
Log in

A QoE handover architecture for converged heterogeneous wireless networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

The convergence of real-time multimedia applications, the increasing coverage of heterogeneous wireless networks and the ever-growing popularity of mobile devices are leading to an era of mobile human-centric multimedia services. In this scenario, heterogeneous communications will co-exist and ensure that the end-user is always best connected. The rigorous networking demands of wireless multimedia systems, beyond quality-oriented control strategies, are necessary to guarantee the best user experience over time. Therefore, the Quality of Experience (QoE) support, especially for 2D or 3D videos in multi-operator environments, remains a significant challenge and is crucial for the success of multimedia systems. This paper proposes a QoE Handover Architecture for Converged Heterogeneous Wireless Networks, called QoEHand. QoEHand extends the Media Independent Handover (MIH)/IEEE 802.21 with QoE-awareness, seamless mobility and video adaptation by integrating a set of QoE-based decision-making modules into MIH, namely a video quality estimator, a dynamic class of service mapping and content adaptation schemes. The QoEHand video estimator, mapping and adaptation components operate by coordinating information about video characteristics, available wireless resources in IEEE 802.11e and IEEE 802.16e service classes, and QoE-aware human experience. The video quality estimator works without the need for any decoding, which saves time and minimises processing overheads. Simulations were carried out to show the benefits of QoEHand and its impact on user perception by using objective and subjective QoE metrics.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Roy, J. J. J., Vaidehi, V., & Sricharan, M. S. (2011). QoS guaranteed integration methodology for a WLAN–WiMAX heterogeneous network. Computers & Electrical Engineering, 37(3), 261–274.

    Article  Google Scholar 

  2. De La Oliva, A., Banchs, A., Soto, I., Melia, T., & Vidal, A. (2008). An overview of IEEE 802.21: media-independent handover services. IEEE Wireless Communications, 15(4), 96–103.

    Article  Google Scholar 

  3. Venkataraman, M., & Chatterjee, M. (2011). Inferring video QoE in real time. IEEE Network, 25(1), 4–13.

    Article  Google Scholar 

  4. Aguiar, E., Riker, A., Mu, M., Zeadally, S., Cerqueira, E., & Abelem, A. (2012). Real-time QoE prediction for multimedia applications in wireless mesh networks. 4th IEEE Future Multimedia Network Workshop/9th IEEE Consumer Communications and Networking Conference, CCNC 2012, Las Vegas, USA.

  5. Al-Surmi, I., Othman, M., & Mohd Ali, B. (2012). Mobility management for IP-based next generation mobile networks: review, challenge and perspective. Journal of Network and Computer Applications, 35(1), 295–315.

    Article  Google Scholar 

  6. Zhang, J., & Ansari, N. (2011). On assuring end-to-end QoE in next generation networks: challenges and a possible solution. IEEE Communications Magazine, 49(7), 185–191.

    Article  Google Scholar 

  7. Sousa, R., Mota, E. S., Silva, E. N., Paixão, K. S., Faria, B. H. C., & Neto, J. B. P. (2010). GoP size influence in high resolution video streaming over wireless mesh network. IEEE Symposium on Computers and Communications, 2010, 1–3.

    Article  Google Scholar 

  8. Huszák, Á., & Imre, S. (2010). Analysing GoP structure and packet loss effects on error propagation in mpeg-4 video streams. 4th International Symposium on Communications, Control and Signal Processing (ISCCSP), 1–5.

  9. Matos, F., Matos, A., Simoes, P., & Monteiro, E. (2011). QoS adaptation in inter-domain services. 12th IFIP/IEEE International Symposium on Integrated Network Management, 257–264.

  10. Aguiar, E. S., Riker, A., Abelem, A., Cerqueira, E, & Mu, M. (2012). Video quality estimator for wireless mesh networks. IEEE/ACM 20th International Workshop on Quality of Service (IEEE/ACM IWQoS 2012), 1–9.

  11. Mu, M., Romaniak, P., Mauthe, A., Leszczuk, M., Janowski, L., & Cerqueira, E. (2012). Framework for the integrated video quality assessment. Multimedia Tools and Applications, 61(3), 787–817.

    Article  Google Scholar 

  12. Keimel, C., Rothbucher, M., Shen, H., & Diepold, K. J. (2011). Video is a cube. IEEE Signal Processing Magazine, 28(6), 41–49.

    Article  Google Scholar 

  13. Mohamed, S., & Rubino, G. (2002). A study of real-time packet video quality using random neural networks. IEEE Transactions on Circuits and Systems for Video Technology, 12(12), 1071–1083.

    Article  Google Scholar 

  14. Ghareeb, M., & Viho, C. (2010). Hybrid QoE assessment is well-suited for multiple description coding video streaming in overlay networks. 8th Annual Communication Networks and Services Research Conference, 327–333.

  15. Cancela, H., Amoza, F. R., Rodríguez-Bocca, P., Rubino, G., & Sabiguero, A. (2008). A robust P2P streaming architecture and its application to a high quality live-video service. Electronic Notes in Discrete Mathematics, 30, 219–224.

    Article  Google Scholar 

  16. Da Silva, A. P. C., Varela, M., de Souza e Silva, E., Leão, R. M. M., & Rubino, G. (2008). Quality assessment of interactive voice applications. Computer Networks, 52(6), 1179–1192.

    Article  Google Scholar 

  17. Rubino, G., Varela, M., & Bonnin, J.-M. (2006). Controlling multimedia QoS in the future home network using the PSQA metric. The Computer Journal, 49(2), 137.

    Article  Google Scholar 

  18. Piamrat, K., Viho, C. G., Bonnin, J.-M. M., & Ksentini, A. (2009). Quality of experience measurements for video streaming over wireless networks. IEEE Sixth International Conference on New Generations in Information Technology, 1184–1189.

  19. Piamrat, K., Ksentini, A., Viho, C. G., & Bonnin, J.-M. M. (2008). QoE-based network selection for multimedia users in IEEE 802.11 wireless networks. 33rd IEEE Conference on Local Computer Networks (LCN 2008), 388–394.

  20. Kim, Y., Pack, S., Kang, C. G., & Park, S. (2011). An enhanced information server for seamless vertical handover in IEEE 802.21 MIH networks. Computer Networks, 55(1), 147–158.

    Article  Google Scholar 

  21. Lim, W.-S., Kim, D.-W., Suh, Y.-J., & Won, J.-J. (2009). Implementation and performance study of IEEE 802.21 in integrated IEEE 802.11/802.16e networks. Computer Communications, 32(1), 134–143.

    Article  Google Scholar 

  22. Zhou, L., Chao, H.-C., & Vasilakos, A. V. (2011). Joint forensics-scheduling strategy for delay-sensitive multimedia applications over heterogeneous networks. IEEE Journal on Selected Areas in Communications, 29(7), 1358–1367.

    Article  Google Scholar 

  23. Lin, C.-P., Chen, H.-L., & Leu, J.-S. (2012). A predictive handover scheme to improve service quality in the IEEE 802.21 network. Computers & Electrical Engineering, 38(3), 681–693.

    Article  Google Scholar 

  24. Brooks, P., & Hestnes, B. (2010). User measures of quality of experience: why being objective and quantitative is important. IEEE Network, 24(2), 8–13.

    Article  Google Scholar 

  25. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323, 533–536.

    Article  Google Scholar 

  26. Recommendation ITU-R BT.500-11. Methodology for the subjective assessment of the quality of television pictures. (2012). http://www.dii.unisi.it/~menegaz/DoctoralSchool2004/papers/ITU-R_BT.500-11.pdf. Accessed March 11, 2013.

  27. VTL. (2012). Video trace library. trace.eas.asu.edu. Accessed March 11, 2013.

  28. Zhenxing, C., & Satoshi, G. (2011). Efficient motion vector prediction algorithm using pattern matching. Journal of Visual Communication and Image Representation, 22(8), 727–733.

    Article  Google Scholar 

  29. Majdi, E., Abdelkrim, E., Samy, E., Jean-Luc, D., & Rached, T. (2012). A low-pow oriented architecture for H.264 variable block size motion estimation based on a resource sharing scheme. The VLSI Journal, Available online 3 October 2012, ISSN 0167-9260, doi:10.1016/j.vlsi.2012.09.001.

  30. Roma, N., & Sousa, L. (2001). A tutorial overview on the properties of the discrete cosine transform for encoded image and video processing. Signal Processing Journal, 91(11), 2443–2464.

    Article  Google Scholar 

  31. Quadros, C., Melo, A., Douglas, A., Abelém, A., Cerqueira, E., Neto, A., Riker, A., & Curado, M. (2012). QoE-based packet drop control for 3D-video streaming over wireless networks. 7th IFIP/ACM Latin American Networking Conference, 59201366.

  32. Zheng, Y., & Meng, Y. (2011). Modular neural networks for multi-class object recognition. IEEE International Conference on Robotics and Automation, 2927–2932.

  33. Choi, H., & Lee, C. H. (2011). Motion adaptive deinterlacing with modular neural networks. IEEE Transactions on Circuits and Systems for Video Technology, 21(6), 844–849.

    Article  Google Scholar 

  34. So-In, C., Jain, R., & Tamimi, A.-K. (2009). Scheduling in IEEE 802.16e mobile WiMAX networks: key issues and a survey. IEEE Journal on Selected Areas in Communications, 27(2), 156–171.

    Article  Google Scholar 

  35. Lee, J.-F. F., Liao, W., Chen, J.-M., & Lee, H.-H. (2009). A practical QoS solution to voice over IP in IEEE 802.11 WLANs. IEEE Communications Magazine, 47(4), 111–117.

    Article  Google Scholar 

  36. Rouil, R., Golmie, N., & Montavont, N. (2010). Media independent handover transport using cross-layer optimized stream control transmission protocol. Computer Communications, 33(9), 1075–1085.

    Article  Google Scholar 

Download references

Acknowledgments

This work was funded by The National Council for Scientific and Technological Development (CNPq). Authors would like to thank PROPESP/FADESP/UFPA. Eduardo Cerqueira receives a CNPq Fellowship.

Author information

Authors and Affiliations

  1. Federal University of Para, Belém, Brazil

    Denis Rosário & Eduardo Cerqueira

  2. Federal University of Rio Grande do Norte, Natal, Brazil

    Augusto Neto

  3. University of Coimbra, Coimbra, Portugal

    Andre Riker, Roger Immich & Marilia Curado

Authors
  1. Denis Rosário
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eduardo Cerqueira
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Augusto Neto
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Andre Riker
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Roger Immich
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Marilia Curado
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Eduardo Cerqueira.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rosário, D., Cerqueira, E., Neto, A. et al. A QoE handover architecture for converged heterogeneous wireless networks. Wireless Netw 19, 2005–2020 (2013). https://doi.org/10.1007/s11276-013-0584-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-013-0584-y

Keywords

Search

Navigation