Crowdsourcing Mobile Internet access chacteristics to improve Video Streaming

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School of Science | Master's thesis
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Date

2011

Department

Tietotekniikan laitos

Major/Subject

Tietokoneverkot

Mcode

T-110

Degree programme

Language

en

Pages

[9] + 85

Series

Abstract

Streaming multimedia over a mobile network consumes much higher bandwidth than either browsing or email. This thesis suggests one possible way to detect network congestion beforehand by means of crowdsourcing to improve the quality of video streaming. Here we design and develop a learning system which learns changes in network congestion from updates sent by mobile clients. The system learns the changes in network capacity at different instants of time at different locations from multiple mobile users. The objective of this learning system is to respond to client requests for network capacity for their future route. The system is able to learn different types of client updates under different learning rates.

Description

Supervisor

Ylä-Jääski, Antti

Thesis advisor

Ott, Jörg
Singh, Varun
Curcio, Igor

Keywords

congestion, map, 3G, mobility, location, bandwidth, streaming, bit rate, downlink, cell loading, capacity

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Citation

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https://urn.fi/URN:NBN:fi:aalto-2020122358019

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[dipl] Perustieteiden korkeakoulu / SCI