Energy-Efficient Video Streaming over Named Data Networking Using Interest Aggregation and Playout Buffer Control

Ishizu, Yuya; Kanai, Kazuaki; Katto, Jiro; Nakazato, Hidenori; Hirose, Masataka

doi:10.1109/dsdis.2015.38

Cited by 7 publications

(1 citation statement)

References 17 publications

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“…This recent strategy can be classified into short (or zippy pacing) and long ON/OFF cycle (or sawtooth pacing) [17]. In our previous paper, we mentioned that the long ON/OFF cycle can contribute to reducing power consumption because the occurrences of tail energy can be reduced [18]. Based on these considerations, we consider an adaptive playout buffer control for reducing power consumption.…”

Section: Proposed Methods and Evaluationsmentioning

confidence: 99%

Methods for Adaptive Video Streaming and Picture Quality Assessment to Improve QoS/QoE Performances

Kanai

Wei

Cheng

et al. 2019

IEICE Trans. Commun.

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Kenji KANAI †a) , Member, Bo WEI †b) , Zhengxue CHENG †c) , Student Members, Masaru TAKEUCHI †d) , Member, and Jiro KATTO †e) , Fellow SUMMARY This paper introduces recent trends in video streaming and four methods proposed by the authors for video streaming. Video traffic dominates the Internet as seen in current trends, and new visual contents such as UHD and 360-degree movies are being delivered. MPEG-DASH has become popular for adaptive video streaming, and machine learning techniques are being introduced in several parts of video streaming. Along with these research trends, the authors also tried four methods: route navigation, throughput prediction, image quality assessment, and perceptual video streaming. These methods contribute to improving QoS/QoE performance and reducing power consumption and storage size.

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Section: Proposed Methods and Evaluationsmentioning

confidence: 99%