Correlating Quality of Experience and Quality of Service for Network Applications

Author:

Ivanovici Mihai1,Beuran Razvan2

Affiliation:

1. Transilvania University of Brasov, România

2. National Institute of Information and Communications Technology & Japan Advanced Institute of Science and Technology, Japan

Abstract

There is a significant difference between what a network application experiences as quality at network level, and what the user perceives as quality at application level. From the network point of view, applications require certain delay, bandwidth and packet loss bounds to be met – ideally zero delay and zero loss. However, users should not be directly concerned with network conditions, and furthermore they are usually neither able to measure nor predict them. Users only expect good application performance, i.e., a fast and reliable file transfer, high quality for voice or video transmission, and so on, depending on the application being used. This is true both in wired as well as wireless networks. In order to understand network application behavior, as well as the interaction between the application and the network, one must perform a delicate task – the one of correlating the Quality of Service (QoS), i.e., the degradation induced at network level (as a measure of what the application experiences), with the Quality of Experience (QoE), i.e., the degradation perceived by the user at application level (as a measure of the user-perceived quality) (Ivanovici, 2006). This is done by simultaneously measuring the QoS degradation and the application QoE on an end-to-end basis. These measures must be then correlated by taking into account their temporal relationship. Assessing the correlation between QoE and QoS makes it possible to predict application performance given a known QoS degradation level, and to determine the QoS bounds that are required in order to attain a desired QoE level.

Publisher

IGI Global

Reference79 articles.

1. Allen, A. O. (1990). Probability, Statistics, and Queueing Theory with Computer Science Applications (2nd ed.). New York: Academic Press.

2. Almes, G., Kalidindi, S., & Zekauskas, M. (1999). A One-way Delay Metric for IPPM. IETF RFC 2679.

3. Almes, G., Kalidindi, S., & Zekauskas, M. (1999). A One-way Packet Loss Metric for IPPM. IETF RFC 2680. Anue Systems. (n.d.). Network Emulation. Retrieved from http://www.anuesystems.com

4. Arlitt, M. F., & Williamson, C. L. (1996). Web Server Workload Characterization: The Search for Invariants. In Proc. SIGMETRICS, Philadelphia, PA, USA.

5. Beuran, R. (2004a). Mesure de la Qualite dans les Reseaux Informatiques. Ph. D. Thesis, Politehnica University of Bucharest, România & Jean Monet University of St. Etienne, France.

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