On performance estimation of prefetching algorithms for streaming content in automotive environments

Author

Protzmann, Robert ; Massow, Kay ; Radusch, Ilja

Author_Institution

Fraunhofer FOKUS, Berlin Automotive Services & Commun. Technol., Berlin, Germany

fYear

2014

fDate

2-4 April 2014

Firstpage

147

Lastpage

147

Abstract

Media streaming in automotive environments is becoming more important with the proliferation of 3G/4G technologies and the general demand for consuming internet content in cars. Especially the rising popularity of Music on Demand and Media Cloud Storage services pushes automotive manufactures efforts to provide decent music streaming capabilities in vehicles. This fact has recently brought car manufactures and music streaming services together. Thanks to today´s mobile broad band Internet connectivity, music streaming is becoming available in the car. Volvo and Ford have announced to pair up with the popular music streaming service Spotify. Ford does already have a partnership with Rhapsody´s music streaming and with the cloud music service Amazon Cloud Player while BMW is going to bring Rara to their vehicles.

Keywords

3G mobile communication; 4G mobile communication; automobiles; media streaming; mobile computing; 3G-4G technologies; Internet content; automotive environment; media cloud storage; media streaming; mobile broad band Internet connectivity; music on demand; music streaming; performance estimation; prefetching algorithm; streaming content; Automotive engineering; Bandwidth; Cloud computing; Mobile communication; Prediction algorithms; Prefetching; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless On-demand Network Systems and Services (WONS), 2014 11th Annual Conference on

Conference_Location

Obergurgl

Type

conf

DOI

10.1109/WONS.2014.6814736

Filename

6814736