绿色流的端到端优化

R. Seeliger, S. Pham, S. Arbanowski
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引用次数: 0

摘要

视频流是一种广泛使用且需要能源的在线服务,它会导致二氧化碳排放和环境问题。在本文中,我们研究了绿色流媒体技术的技术可行性和效益,旨在优化整个供应链的流媒体内容的能源效率和碳足迹。我们的工作集中在三个关键技术:上下文感知编码、绿色媒体播放器和能源感知内容引导。我们提出了实验和模拟来评估这些技术的性能和影响。我们还探讨了它们在流媒体行业创造新商机的经济可行性和潜力。我们的工作提供了对绿色流技术的全面评估,可以支持全球气候行动和环境保护的努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
End-to-end Optimizations for Green Streaming
Video streaming is a widely used and energy-demanding online service, which contributes to CO2 emissions and environmental issues. In this paper, we investigate the technological feasibility and benefits of green streaming technologies, which aim to optimize the energy efficiency and carbon footprint of streaming content across the whole supply chain. Our work focuses on three key technologies: context-aware encoding, green media players, and energy-aware content steering. We present experiments and simulations to evaluate the performance and impact of these technologies. We also explore their economic viability and potential for creating new business opportunities in the streaming industry. Our work provides a holistic evaluation of green streaming technologies, which can support the global efforts for climate action and environmental protection.
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