科研之友
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摘要
Video streaming has become one of the most popular networked applications and, with the increased bandwidth and computation power of mobile devices, anywhere and anytime streaming has become a reality. Unfortunately, it remains a challenging task to compress high-quality video in real-time in such devices given the excessive computation and energy demands of compression. On the other hand, transmitting the raw video is simply unaffordable from both energy and bandwidth perspective. In this paper, we propose DualEMC, a novel cloud-assisted video compression mechanism for mobile devices. DualEMC leverages the abundant cloud server resources for motion estimation (ME), which is known to be the most computation-intensive step in video compression, accounting for over 90 % of the computation time. With DualEMC, a mobile device selects and uploads only the key information of each picture frame to cloud servers for mesh-based ME, eliminating most of the local computation operations. We develop smart algorithms to identify the key mesh nodes, resulting in minimum distortion and data volume for uploading. Our simulation results demonstrate that DualEMC saves almost 30 % energy for video compression and transmission.
- 出版日期2015-9
- 单位华中科技大学
