| Autor: |
Jonathon Edstrom, Yifu Gong, Ali Ahmad Haidous, Brittney Humphrey, Mark E. Mccourt, Yiwen Xu, Jinhui Wang, Na Gong |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 7, Pp 47479-47493 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2019.2908997 |
| Popis: |
Mobile devices are becoming ever more popular for streaming videos, which account for the majority of all the data traffic on the Internet. Memory is a critical component in mobile video processing systems, increasingly dominating the power consumption. Today, memory designers are still focusing on hardware-level power optimization techniques, which usually come with significant implementation cost (e.g., silicon area overhead or performance penalty). In this paper, we propose a video content-aware memory technique for power-quality tradeoff from viewer's perspectives. Based on the influence of video macroblock characteristics on the viewer's experience, we develop two simple and effective models-decision tree and logistic regression to enable hardware adaptation. We have also implemented a novel viewer-aware bit-truncation technique which minimizes the impact on the viewer's experience, while introducing energy-quality adaptation to the video storage. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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