Presentation 2013-11-15
A Study of Mobile Performance Prediction to Control Wasteful Video Delivery toward GreenICN
Haruki Izumikawa, Hidenori Konishi, Jiro Katto,
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Abstract(in English) With the increasing demand for the energy-efficient communications, we have been tackling the research on the efficient video delivery and caching technologies over ICN (Information Centric Network) as one of the research items of the GreenlCN (Architecture and Applications of Green Information Centric Networking) project. One way to make the video delivery more efficient would be to cut down on the packet losses during the delivery. Since the actual available throughput that is lower than the video delivery rate causes the packet losses, the efficient video delivery can be realized by deducing the actual throughput. In this paper, we propose the mobile performance prediction method where the throughput is predicted based on the two criteria. One is the throughput that is estimated based on the observed radio signal quality. The other is the estimated throughput based on the history of the connected base station and time to access. In addition, we show some results of the two months-long experiment measuring hourly fluctuation in throughput.
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Keyword(in English) Throughput prediction / Video delivery
Paper # NS2013-131
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Committee NS
Conference Date 2013/11/7(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Study of Mobile Performance Prediction to Control Wasteful Video Delivery toward GreenICN
Sub Title (in English)
Keyword(1) Throughput prediction
Keyword(2) Video delivery
1st Author's Name Haruki Izumikawa
1st Author's Affiliation Graduate School of Fundamental Science and Engineering, Waseda University()
2nd Author's Name Hidenori Konishi
2nd Author's Affiliation Graduate School of Fundamental Science and Engineering, Waseda University
3rd Author's Name Jiro Katto
3rd Author's Affiliation Graduate School of Fundamental Science and Engineering, Waseda University
Date 2013-11-15
Paper # NS2013-131
Volume (vol) vol.113
Number (no) 292
Page pp.pp.-
#Pages 4
Date of Issue