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

 
: Protzmann, Robert; Massow, Kay; Radusch, Ilja

:
Postprint urn:nbn:de:0011-n-3037339 (34 KByte PDF)
MD5 Fingerprint: a486c17c1eb89fcee1dd3c8a52eb5d5e
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Created on: 27.8.2014


Institute of Electrical and Electronics Engineers -IEEE-; International Federation for Information Processing -IFIP-:
11th IEEE/IFIP Annual Conference on Wireless On-demand Network Systems and Services, WONS 2014. Proceedings : 2 - 4 April 2014, Obergurgl, Austria
Piscataway, NJ: IEEE, 2014
ISBN: 978-1-4799-4937-3
pp.147
Conference on Wireless On-Demand Network Systems and Services (WONS) <11, 2014, Obergurgl>
English
Conference Paper, Electronic Publication
Fraunhofer FOKUS ()
automotive

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.

: http://publica.fraunhofer.de/documents/N-303733.html