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Data Utility Cognitive Green Video Streaming

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Authors
Kim, Seohyang; Oh, Hayoung; Kim, Chongkwon
Issue Date
2016-01-19
Publisher
KIISE
Citation
2016 International Conference on Big Data and Smart Computing ,
Keywords
Data Utility Cognitive Green Video Streaming공학
Abstract
To optimize resource usage in communication, various algorithms have been proposed to enhance efficiency in data, energy, and throughput. Here we propose a data utility cognitive green video streaming strategy with novel streaming-chunk scheduling algorithm to balance data efficiency and energy efficiency. We focused on maximizing the ratio of data utility to electricity. Simulation study results showed that our proposed strategy could reduce 10~70% data waste while consuming almost the same amount of energy compared to the latest and the most efficient solution considering both data and energy. In addition, it increased the ratio of data utility to electricity. Since our strategy uses simple algorithm with a divide and conquer approach avoiding too many multiplication operators, it requires only 14 percent of calculation time compared to the currently available best strategy.
ISSN
2375-9356
URI
https://hdl.handle.net/10371/116854
DOI
https://doi.org/10.1109/BIGCOMP.2016.7425937
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Computer Science and Engineering (컴퓨터공학부)Others_컴퓨터공학부
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