Large-Scale Measurement of Real-Time Communication on the Web

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.advisorSarolahti, Pasi
dc.contributor.authorLi, Shaohong
dc.contributor.schoolSähkötekniikan korkeakoulufi
dc.contributor.supervisorÖstergård, Patric
dc.date.accessioned2017-12-18T11:49:00Z
dc.date.available2017-12-18T11:49:00Z
dc.date.issued2017-12-11
dc.description.abstractWeb Real-Time Communication (WebRTC) is getting wide adoptions across the browsers (Chrome, Firefox, Opera, etc.) and platforms (PC, Android, iOS). It enables application developers to add real-time communications features (text chat, audio/video calls) to web applications using W3C standard JavaScript APIs, and the end users can enjoy real-time multimedia communication experience from the browser without the complication of installing special applications or browser plug-ins. As WebRTC based applications are getting deployed on the Internet by thousands of companies across the globe, it is very important to understand the quality of the real-time communication services provided by these applications. Important performance metrics to be considered include: whether the communication session was properly setup, what are the network delays, packet loss rate, throughput, etc. At Callstats.io, we provide a solution to address the above concerns. By integrating an JavaScript API into WebRTC applications, Callstats.io helps application providers to measure the Quality of Experience (QoE) related metrics on the end user side. This thesis illustrates how this WebRTC performance measurement system is designed and built and we show some statistics derived from the collected data to give some insight into the performance of today’s WebRTC based real-time communication services. According to our measurement, real-time communication over the Internet are generally performing well in terms of latency and loss. The throughput are good for about 30% of the communication sessions.en
dc.ethesisidAalto 9662
dc.format.extent49+2
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/29181
dc.identifier.urnURN:NBN:fi:aalto-201712187979
dc.language.isoenen
dc.locationP1fi
dc.programmeCCIS - Master’s Programme in Computer, Communication and Information Sciences (TS2013)fi
dc.programme.majorCommunications Engineeringfi
dc.programme.mcodeELEC3029fi
dc.subject.keywordmeasurementen
dc.subject.keywordquality of experienceen
dc.subject.keywordreal-time communicationsen
dc.subject.keywordWebRTCen
dc.titleLarge-Scale Measurement of Real-Time Communication on the Weben
dc.typeG2 Pro gradu, diplomityöfi
dc.type.ontasotMaster's thesisen
dc.type.ontasotDiplomityöfi
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
master_Li_Shaohong_2017.pdf
Size:
1.24 MB
Format:
Adobe Portable Document Format