Title :
ePF-DASH: Energy-efficient prefetching based dynamic adaptive streaming over HTTP
Author :
Seohyang Kim ; Hayoung Oh ; Chongkwon Kim
Author_Institution :
Dept. of Comput. Sci., Seoul Nat. Univ., Seoul, South Korea
Abstract :
CISCO VNI predicted an average annual growth rate of 69.1% for mobile video traffic between 2013 and 2018 and accordingly much academic research related to video streaming has been initiated. In video streaming, Adaptive Bitrate (ABR) is a streaming technique in which a source video is stored on a server at variable encoding rates and each streaming user requests the most appropriate video encoding rate from the server considering their channel capacity or signal power. However, these days, ABR related studies are only focusing on real-time rate adaptation and omitting efficiency in terms of energy. These methods do not consider the energy limited characteristics of mobile devices, which cause dissatisfaction to the streaming users. In this paper, we propose an energy efficient prefetching based dynamic adaptive streaming technique by considering the limited characteristics of the batteries used in mobile devices, in order to reduce the energy waste and provide a similar level of service in terms of the average video rate compared to the latest ABR streaming technique which does not consider the energy consumption.
Keywords :
mobile communication; power aware computing; storage management; telecommunication traffic; transport protocols; video coding; video streaming; ABR; CISCO VNI; adaptive bitrate; average video rate; ePF-DASH; energy consumption; energy efficient prefetching based dynamic adaptive streaming over HTTP; energy limited characteristics; energy waste reduction; mobile devices; mobile video traffic; source video; variable encoding rates; video streaming technique; Bit rate; Encoding; Energy efficiency; Mobile communication; Mobile handsets; Prefetching; Streaming media; ABR; Energy Efficient Communication; MPEG-DASH; Mobile Network; Video Streaming;
Conference_Titel :
Big Data and Smart Computing (BigComp), 2015 International Conference on
Conference_Location :
Jeju
DOI :
10.1109/35021BIGCOMP.2015.7072821