Effect of Network OFF Times on Web Browsing QoE
Independent thesis Advanced level (degree of Master (Two Years))Student thesisAlternative title
Effect of Network OFF Times on Web Browsing QoE (Swedish)
The web user usually expects a better Quality of Service (QoS) from the Internet Service Provider (ISP) for the best Quality of Experience (QoE). User satisfaction and feedback is one of the most important factors for the service providers to determine their QoS and improve the network performance. Service providers are more interested in QoE to provide a better service to their users to maintain their customers in the competitive market. Since there is no much study work conducted in the QoE on web browsing, only a few studies are available for getting user feedbacks. So the ISP is facing a difficulty in the assessment of the user experience in the real time network. Network level performance can be measured by the ISP for QoS and user feedback can be measured for QoE. There is no study available on relating both the QoS and QoE. Relating the network level performance and the user perception is a difficult task for the service providers. In this study we have correlated both the network level traffic performance and user experience. In our experiment the user QoE is tested by applying various off times applied to some specific packets. Our main aim is to evaluate the network level performance and correlate it with the user feedback. Later, on focusing the network level performance network traffic is analyzed for different sessions with off times applied in DNS response, Base file response and Object response. We have discussed in the results by correlating the different sessions of off times that we applied and user feedback MOS. We have also discussed the relation of the network off time in the network with the number of requests sent from client to server and the number of flag bits like SYN & ACK, FIN & ACK and RST flags between the client and server. In this study we also discussed about the user feedback and how the user suffers on varying long response time. Finally, we conclude from our results about the major factor that affects the user feedback and the user interest in using the service again.
Place, publisher, year, edition, pages
2013. , 60 p.
Network performance, Quality of Experience, Mean opnion score, Subjective and Objective measurements
Computer Science Telecommunications
IdentifiersURN: urn:nbn:se:bth-3420Local ID: oai:bth.se:arkivexD2F7728EF2D514F6C1257C0D00315222OAI: oai:DiVA.org:bth-3420DiVA: diva2:830726
chakri PH: +9180083162692015-04-222013-10-232015-06-30Bibliographically approved