Development of a QoE Model

1. Development of a QoE Model Himadeepa Karlapudi 03/07/03

2. What is Quality of Experience (QoE)? • Why do we need QoE ?

3. How is QoE measured? • Predicting TCP throughput and obtaining other network observables • Converting network observables into representative inputs for the QoE model. • The QoE model gets these inputs and conveys the predicted QoE.

4. Predicting TCP throughput • Development of a model that is representative of majority of TCP traffic on the internet. • Three models have been used as a basis for the development of the new model . • Amherst Model • Roch Guerin’s Model • Cardwell’s Model

5. Parameters considered for the development of the model • Network environment and nature of flows • Startup effects • Losses during connection establishment • Acknowledgement type • Inference of packet loss • Assumptions about loss

6. Cont. • Receiver and Sender buffering limitation • Congestion Control Algorithm • Maximum Congestion Window • Delayed acks • Retransmission timeout • Initial congestion window • Other assumptions

7. Simulation Environment Ping ,WRT, SNMP ,MRTG Test client 100Mbps Router 100Mbps server client Link Capacity 10 Mbps or 1.5 Mbps

8. SURGE • Scalable URL Reference Generator • SURGE is used to generate a sequence of URL requests • SURGE consists of three main parts • Client set up • Server set up • Client request generator

9. SURGE (cont.) • The SURGE client setup spawns a number of threads each of which behaves like an individual client. • The client request generator makes the requests for files from the server. • The server setup generates the set of files which are requested by SURGE clients.

10. SURGE (cont.) • As it’s output SURGE gives the start time and end time of each client process. • We can also obtain the mean and variance of server throughput and the total amount of data transferred by the server in unit time. • SURGE can be modified to obtain statistics at regular intervals instead of waiting for the completion of entire simulation.

11. Development of QoE model • Two major issues are involved in the development of QoE model • How should the network be sampled (non invasive sampling) • Transforming these raw samples into input parameters of the chosen model (WRT metric)

12. Sampling Techniques • We use non invasive network sampling where in the network element itself communicates its status (statistics) to the network manager instead of examining tcpdump traces . • Sampling is mostly done at network level and not at application level.

13. Non invasive sampling techniques • Probing: Probes can be implemented using ping packets . We can obtain an estimate of RTT and loss rates. • Polling: This refers to periodic querying by SNMP MIBs maintained in routers to retrieve performance data.

14. Development of QoE model • Once this raw data is obtained this has to fed into a QoE model. • We use a simple WRT metric to obtain QoE initially. The WRT metric gives a variation in the response time. • Our QoE model should be able to predict the mean sample time and also it’s variation.

15. Future work • Comparison of non-invasive and invasive sampling techniques • Impact of congestion control/ avoidance algorithm on the assessment of metrics • Once this is done we assess how our predicted QoE is correlated to the QoE perceived by the user.

16. Future work • Develop a survey methodology to help us validate our assessment algorithm (i.e., have a set of users tell us what they think of their web browsing experience when the WRT metric is 2.5 seconds). • Use the results of this survey to further strengthen the algorithm and make the metrics as close as possible to the quality perceived by end user. • to validate the QoE assessment

17. Future work • Possibly extend Surge to model streaming or conferencing flows • Compare Surge traffic with other approaches to generating realistic traffic loads • Extend the QoE model to Real time applications.