Abstract
This paper investigates the issue of Quality of Experience (QoE) for multimedia services over heterogeneous networks. A new concept of “Isomorphism Flow” (iFlow) was introduced for analyzing multimedia traffics, which is inspired by the abstract algebra based on experimental research. By using iFlow, the multimedia traffics with similar QoE requirements for different users are aggregated. A QoE evaluation method was also proposed for the aggregated traffics. Then a new cross-domain QoE guarantee method based on the iFlow QoE is proposed in this paper to adjust the network resource from the perspective of user perception. The proposed scheme is validated through simulations. Simulation results show that the proposed scheme achieves an enhancement in QoE performance and outperforms the existing schemes.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Karaadi, A., Sun, L., Mkwawa, I.-H.: Multimedia communications in Internet of Things QoT or QoE. In: 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), pp. 23–29 (2017)
Wang, Z., Dong, Y., Mao, S., Wang, X.: Internet multimedia traffic classification from QoS perspective using semi-supervised dictionary learning models. IEEE/CIC China Commun. 14(10), 202–218 (2017)
Wang, Z., Mao, S., Yang, L., Tang, P.: A survey of multimedia big data. IEEE/CIC China Commun. 15(1), 155–176 (2018)
Naserian, E., Wang, X., Dahal, K., Wang, Z., Wang, Z.: Personalized location prediction for group travellers from spatial-temporal trajectories. Future Gener. Comput. Syst. 24(1), 1–15 (2018)
Wang, W., Wang, Q.: Price the QoE, not the data: SMP-economic resource allocation in wireless multimedia Internet of Things. IEEE Commun. Mag. 56(9), 74–79 (2018)
Li, M., Si, P., Zhang, Y.: Delay-tolerant data traffic to software-defined vehicular networks with mobile edge computing in smart city. IEEE Trans. Veh. Technol. (Early Access) 67, 1–14 (2018)
He, X., Wang, K., Huang, H., Miyazaki, T., Wang, Y., Guo, S.: Green resource allocation based on deep reinforcement learning in content-centric IoT. IEEE Trans. Emerg. Top. Comput. (Early Access), 1 (2018)
Nightingale, J., Salva-Garcia, P., Calero, J.M.A., Wang, Q.: 5G-QoE: QoE modeling for ultra-HD video streaming in 5G networks. IEEE Trans. Broadcast. 64(2), 621–634 (2018)
Charonyktakis, P., Plakia, M., Tsamardinos, I., Papadopouli, M.: On user-centric modular QoE prediction for VoIP based on machine-learning algorithms. IEEE Trans. Mob. Comput. 15(6), 1443–1456 (2016)
Murray, N., Lee, B., Qiao, Y., Miro-Muntean, G.: The impact of scent type on olfaction-enhanced multimedia quality of experience. IEEE Trans. Syst. Man Cybern.: Syst. 47(9), 2503–2515 (2017)
Tao, X., Dong, L., Li, Y., Zhou, J., Ge, N., Jianhua, L.: Real-time personalized content catering via viewer sentiment feedback: a QoE perspective. IEEE Netw. 29(6), 14–19 (2015)
Scott, M.J., Guntuku, S.C., Lin, W., Ghinea, G.: Do personality and culture influence perceived video quality and enjoyment. IEEE Trans. Multimed. 18(9), 1796–1807 (2016)
Mitra, K., Zaslavsky, A., Åhlund, C.: Context-aware QoE modelling, measurement, and prediction in mobile computing systems. IEEE Trans. Mob. Comput. 14(5), 920–936 (2015)
Chen, B.-W., Ji, W., Jiang, F., Rho, S.: QoE-enabled big video streaming for large-scale heterogeneous clients and networks in smart cities. IEEE Access 4(1), 97–107 (2016)
Chen, Y., Kaishun, W., Zhang, Q.: From QoS to QoE: a tutorial on video quality assessment. IEEE Commun. Surv. Tutor. 7(2), 1126–1165 (2015)
ITU-T Recommendation P.913. Methods for the subjective assessment of video quality, audio quality and audiovisual quality of Internet video and distribution quality television in any environment (2014)
ITU-R Recommendation BT.500-11. Methodology for the subjective assessment of the quality of television pictures (2002)
Takahashi, A., Hands, D., Barriac, V.: Standardization activities in the ITU for a QoE assessment of IPYV. IEEE Commun. Mag. 46(2), 78–84 (2008)
Wang, Z.J., Dong, Y.N., Wang, X.: A dynamic service class mapping scheme for different QoS domains using flow aggregation. IEEE Syst. J. 9(4), 1299–1310 (2015)
Acknowledgment
This work was supported in part by National Natural Science Foundation of China (No. 61401004).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Wang, Z., Chen, C., Wang, X., Yang, L., Tang, P. (2019). New Cross-Domain QoE Guarantee Method Based on Isomorphism Flow. In: Gao, H., Wang, X., Yin, Y., Iqbal, M. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-030-12981-1_30
Download citation
DOI: https://doi.org/10.1007/978-3-030-12981-1_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-12980-4
Online ISBN: 978-3-030-12981-1
eBook Packages: Computer ScienceComputer Science (R0)