UMBU: Um Framework para Experimentação e Avaliação de QoE em Transmissões Multimídia
Resumo
Dentre as principais soluções disponíveis para análise de Qualidade de Experiência (QoE) em transmissões multimídia, o EvalVid se apresenta como a principal referência em código aberto dessa área. No entanto, esta ferramenta possui inúmeras deficiências, que vão desde a instalação até a análise do QoE, impondo sérias restrições que limitam a operacionalização de avaliações em larga escala. Em vista disso, este trabalho propõe um avanço no campo da experimentação de QoE em transmissões multimídia através do Unified Multimedia-based Network Evaluation Platform (UMBU), um framework para experimentação e avaliação cujo objetivo é fornecer uma interface que possibilita acesso ubíquo para o gerenciamento refinado sobre as operações relacionadas aos experimentos, além de prover uma série de mecanismos que possibilitam a realização de múltiplas avaliações de maneira escalável e flexível.
Referências
Boucadairm, M. and Jacquenet, C. (2014). Software-Dened Networking: A Perspective from within a Service Provider Environment. Internet Engineering Task Force Request for Comments (RFC 7149).
Bouras, C., Charalambides, S., Drakoulelis, M., Kioumourtzis, G., and Stamos, K. (2013). Simulation design and execution-the case of tral. In SIMULTECH, pages 27–34.
Chen, Y., Wu, K., and Zhang, Q. (2015). From QoS to QoE: A tutorial on video quality assessment. IEEE Communications Surveys & Tutorials, 17(2):1126–1165.
Chikkerur, S., Sundaram, V., Reisslein, M., and Karam, L. J. (2011). Objective video quality assessment methods: A classication, review, and performance comparison. IEEE transactions on broadcasting, 57(2):165–182.
Cisco, C. V. N. I. (2017). Global mobile data trafc forecast update, 2016–2021 white paper, 2017.
Clark, A., Wu, Q., Schott, R., and Zorn, G. (2014). RTP Control Protocol (RTCP) Extended Report (XR) Blocks for Mean Opinion Score (MOS) Metric Reporting. Internet Engineering Task Force Request for Comments (RFC 7266).
Gaubatz, M. and Hemami, S. (2011). Metrix mux visual quality assessment package. http://www.foulard.ece.cornell.edu/gaubatz/metrixmux.
Ke, C.-H., Lin, C.-H., Shieh, C.-K., and Hwang, W.-S. (2006). A novel realistic simulation tool for video transmission over wireless network. In Sensor Networks, Ubiquitous, and Trustworthy Computing, 2006. IEEE International Conference on, volume 1, pages 7–pp. IEEE.
Ke, C.-H., Shieh, C.-K., Hwang, W.-S., and Ziviani, A. (2008). An evaluation framework for more realistic simulations of mpeg video transmission. Journal of Information Science & Engineering, 24(2).
Klaue, J., Rathke, B., and Wolisz, A. (2003). Evalvid–a framework for video transmission and quality evaluation. In International Conference on Modelling Techniques and Tools for Computer Performance Evaluation, pages 255–272. Springer.
Krasula, L., Klíma, M., Rogard, E., and Jeanblanc, E. (2011). Matlab-based applications for image processing and image quality assessment–part i: Software description. Radioengineering, 20(4):1009–1015.
Mijumbi, R., Serrat, J., Gorricho, J. L., Bouten, N., Turck, F. D., and Boutaba, R. (2016). Network function virtualization: State-of-the-art and research challenges. IEEE Communications Surveys Tutorials, 18(1):236–262.
Murthy, A. V. and Karam, L. J. (2010). A matlab-based framework for image and video quality evaluation. In Quality of Multimedia Experience (QoMEX), 2010 Second International Workshop on, pages 242–247. IEEE.
Silva, F. S. D., Neto, A. V., Maciel, D., Castillo-Lema, J., Silva, F., Frosi, P., and Cerqueira, E. (2016). An innovative software-dened winemo architecture for advanced qos-guaranteed mobile service transport. Computer Networks, 107:270–291.
Vatolin, D., Moskvin, A., Petrov, O., and Trunichkin, N. (2009). MSU Video Quality Measurement Tool.
Wang, Z., Sheikh, H. R., Bovik, A. C., et al. (2003). Objective video quality assessment. The handbook of video databases: design and applications, 41:1041–1078.
Bouras, C., Charalambides, S., Drakoulelis, M., Kioumourtzis, G., and Stamos, K. (2013). Simulation design and execution-the case of tral. In SIMULTECH, pages 27–34.
Chen, Y., Wu, K., and Zhang, Q. (2015). From QoS to QoE: A tutorial on video quality assessment. IEEE Communications Surveys & Tutorials, 17(2):1126–1165.
Chikkerur, S., Sundaram, V., Reisslein, M., and Karam, L. J. (2011). Objective video quality assessment methods: A classication, review, and performance comparison. IEEE transactions on broadcasting, 57(2):165–182.
Cisco, C. V. N. I. (2017). Global mobile data trafc forecast update, 2016–2021 white paper, 2017.
Clark, A., Wu, Q., Schott, R., and Zorn, G. (2014). RTP Control Protocol (RTCP) Extended Report (XR) Blocks for Mean Opinion Score (MOS) Metric Reporting. Internet Engineering Task Force Request for Comments (RFC 7266).
Gaubatz, M. and Hemami, S. (2011). Metrix mux visual quality assessment package. http://www.foulard.ece.cornell.edu/gaubatz/metrixmux.
Ke, C.-H., Lin, C.-H., Shieh, C.-K., and Hwang, W.-S. (2006). A novel realistic simulation tool for video transmission over wireless network. In Sensor Networks, Ubiquitous, and Trustworthy Computing, 2006. IEEE International Conference on, volume 1, pages 7–pp. IEEE.
Ke, C.-H., Shieh, C.-K., Hwang, W.-S., and Ziviani, A. (2008). An evaluation framework for more realistic simulations of mpeg video transmission. Journal of Information Science & Engineering, 24(2).
Klaue, J., Rathke, B., and Wolisz, A. (2003). Evalvid–a framework for video transmission and quality evaluation. In International Conference on Modelling Techniques and Tools for Computer Performance Evaluation, pages 255–272. Springer.
Krasula, L., Klíma, M., Rogard, E., and Jeanblanc, E. (2011). Matlab-based applications for image processing and image quality assessment–part i: Software description. Radioengineering, 20(4):1009–1015.
Mijumbi, R., Serrat, J., Gorricho, J. L., Bouten, N., Turck, F. D., and Boutaba, R. (2016). Network function virtualization: State-of-the-art and research challenges. IEEE Communications Surveys Tutorials, 18(1):236–262.
Murthy, A. V. and Karam, L. J. (2010). A matlab-based framework for image and video quality evaluation. In Quality of Multimedia Experience (QoMEX), 2010 Second International Workshop on, pages 242–247. IEEE.
Silva, F. S. D., Neto, A. V., Maciel, D., Castillo-Lema, J., Silva, F., Frosi, P., and Cerqueira, E. (2016). An innovative software-dened winemo architecture for advanced qos-guaranteed mobile service transport. Computer Networks, 107:270–291.
Vatolin, D., Moskvin, A., Petrov, O., and Trunichkin, N. (2009). MSU Video Quality Measurement Tool.
Wang, Z., Sheikh, H. R., Bovik, A. C., et al. (2003). Objective video quality assessment. The handbook of video databases: design and applications, 41:1041–1078.
Publicado
06/05/2018
Como Citar
DE AZEVEDO, Carlos; P. NETO, Emídio; DOS SANTOS, Charles; SILVA, Felipe; VENÂNCIO NETO, Augusto.
UMBU: Um Framework para Experimentação e Avaliação de QoE em Transmissões Multimídia. In: SALÃO DE FERRAMENTAS - SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 1. , 2018, Campos do Jordão.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc_estendido.2018.14167.
