A TEFSM-based Framework for QoE Evaluation of OTT Services

Most of the work related to QoE maps objective variables (QoS-related) into a single one that predicts the quality the user perceives. In this paper we present a new approach to model multimedia OTT services, integrating not only the functional aspects of the service but also non-functional variables, which are classified into objective, subjective and business-related. Non-functional metrics might affect the Quality of Service (QoS), Quality of Experience (QoE) and Quality of Business (QoBiz) correspondingly. We also discuss how all these variables can be taken into account to predict the QoE of the service being studied. The functional requirements are modeled into a Timed Extended Finite State Machine (TEFSM), which is augmented with context variables (and their updating functions) representing non-functional requirements related to QoS, QoE and QoBiz. We use these parameters to evaluate the QoE using a trace model derived from the TEFSM previously built.

quality of service (qos), quality of experience (qoe), quality of business (qobiz), ott service, formal model, time extended finite state machine (tefsm)

1. Société beIN Sports France, beIN Sports Connect, https://beinsportsconnect.fr/index.fr. 2014, (Accessed August 2014).

2. Wolter K., Van Moorsel A. The relationship between Quality of Service and Business Metrics: monitoring, notification and optimization. Hewlett-Packard Labs Technical Report HPL-2001-96, 2001.

3. Schatz R., Hoßfeld T., Janowski L., Egger S. From packets to people: Quality of experience as a new measurement challenge, LNCS, 2013, vol. 7754, pp. 219-263.

4. Geerts D., De Moor K., Ketykó I., Jacobs A., Van den Bergh J., Joseph W., Martens L., De Marez L. Linking an integrated framework with appropriate methods for measuring QoE. Second International Workshop on Quality of Multimedia Experience, 2010, pp. 158-163.

5. Green W., Lancaster B., Sladek J. Over-the-top Services. http://www.pipelinepub.com/1207/pdf/Article_3.pdf, 2006 (Accessed August 2014).

6. Van Moorsel A. Metrics for the Internet age: Quality of Experience and Quality of Business. Fifth International Workshop on Performability Modeling of Computer and Communication Systems, 2001, pp. 26-31, Universität Erlangen-Nürnberg, Germany.

7. ITU. Vocabulary for performance and quality of service. Recommendation P.10/G.100, July 2006.

8. Gozdecki J., Jajszczyk A., Stankiewicz R. Quality of service terminology in IP networks, IEEE Communications Magazine, 2003, vol. 41, pp. 153-159.

9. Le Callet P., Möller S., Perkis A. Qualinet whitepaper on definitions of quality of experience. Seminar report, European Network on Quality of Experience in Multimedia Systems and Services, June 2012.

10. Stojanovic M., Factors affecting service provider’s quality of business in NGN environment. Center for Quality, 2012.

11. Cheng K. T., Krishnakumar A. S. Automatic functional test generation using the extended finite state machine model, in Proceedings of the 30th International Design Automation Conference, 1993, pp. 86-91.

12. Petrenko A., Boroday S., Groz R. Confirming configurations in EFSM testing. IEEE Transactions on Software Engineering, 2004, vol. 30, pp. 29-42.

13. Andrews A. A., Offutt J., Alexander R. T. Testing web applications by modeling with FSMs. Software & Systems Modeling, 2005, vol. 4, no. 3, pp. 326-345.

14. Laghari K., Connelly K. Toward total quality of experience: A QoE model in a communication ecosystem. IEEE Communications Magazine, 2012, vol. 50, pp. 58-65.

15. Aaker D. A. Measuring brand equity across products and markets. California management review, 1996, vol. 38, no. 3, pp. 102-120.

16. Sandoval J., Ehijo A., Casals A., Estevez C. New model and open tools for real testing of QoE in mobile broadband services and the transport protocol impact: The operator’s approach. IEEE Latin-America Conference on Communications (LATINCOM), 2013, pp. 1-5.