QoS/QoE Mapping and Adjustment Model in the Cloud-based Multimedia Infrastructure

被引:34
作者
Hsu, Wu-Hsiao [1 ]
Lo, Chi-Hsiang [2 ,3 ]
机构
[1] Ming Chuan Univ, Dept Comp Sci & Informat Engn, Tao Yuan, Taiwan
[2] Natl Ilan Univ, Inst Comp Sci & Informat Engn, Ilan City, Taiwan
[3] Natl Ilan Univ, Dept Elect Engn, Ilan City, Taiwan
来源
IEEE SYSTEMS JOURNAL | 2014年 / 8卷 / 01期
关键词
Diffserv-aware multicast tree (DAMT); genetic algorithm (GA); quality of service (QoS)/quality of experience (QoE) model; simulated streaming video platform; QOE; QUALITY; EXPERIENCE;
D O I
10.1109/JSYST.2013.2253035
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The quality of service (QoS) requirement and multicast service support from IP networks are two important factors for providing cloud-based multimedia services. However, QoS lacks an important element in characterizing multimedia services, namely, user perception. In this paper, we propose a QoS to quality of experience (QoE) mapping and adjustment model to translate the network QoS parameters into the user's QoE in the cloud-based multimedia infrastructure. The model is composed of three parts: QoE function, practical measurement and statistical analysis, and a simulated streaming video platform. We first discuss how to design the QoE function, and then use the practical measurement and statistical analysis to derive the optimum values of eight QoE parameters in the proposed QoE function. To map the network QoS parameters into the user's QoE, a simulated streaming video platform is used to denote a cloud-based multimedia infrastructure. Each multicast member that has guaranteed bandwidth in the simulated streaming video platform uses the QoE function to calculate its QoE score after watching the streaming video. If the QoE score is less than a derived lower bound value, it means that one of the multicast members has a low QoE. In this situation, the genetic algorithm is enabled to adjust the constructed diffserv-aware multicast tree to respond quickly to the degradation of QoE. The simulation results show that the user's QoE and network QoS are consistent with each other.
引用
收藏
页码:247 / 255
页数:9
相关论文
共 19 条
  • [11] Improving End-to-End QoE via Close Cooperation between Applications and ISPs
    Mathieu, Bertrand
    Ellouze, Selim
    Schwan, Nico
    Griffin, David
    Mykoniati, Eleni
    Ahmed, Toufik
    Prats, Oriol Ribera
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2011, 49 (03) : 136 - 143
  • [12] Murphy S., DIFFSERV ADDITIONS N
  • [13] Patidar S., 2012, Proceedings of the 2012 Second International Conference on Advanced Computing & Communication Technologies (ACCT 2012), P394, DOI 10.1109/ACCT.2012.15
  • [14] 13 WAYS TO LOOK AT THE CORRELATION-COEFFICIENT
    RODGERS, JL
    NICEWANDER, WA
    [J]. AMERICAN STATISTICIAN, 1988, 42 (01) : 59 - 66
  • [15] Szymanski T. H., 2011, P IEEE 19 INT WORKSH, P1
  • [16] Inferring Video QoE in Real Time
    Venkataraman, Mukundan
    Chatterjee, Mainak
    [J]. IEEE NETWORK, 2011, 25 (01): : 4 - 13
  • [17] Ventakaraman M., 2010, P IEEE GLOBECOM MIAM, P1
  • [18] An Approach to Modeling and Control of QoE in Next Generation Networks
    Volk, Mojca
    Sterle, Janez
    Sedlar, Urban
    Kos, Andrej
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2010, 48 (08) : 126 - 135
  • [19] Flooding-limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs
    Yen, Yun-Sheng
    Chao, Han-Chieh
    Chang, Ruay-Shiung
    Vasilakos, Athanasios
    [J]. MATHEMATICAL AND COMPUTER MODELLING, 2011, 53 (11-12) : 2238 - 2250