DualEMC: energy efficient mobile multimedia communication with cloud

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• 作者：Yuan Zhao ; Lei Zhang ; Xiaoqiang Ma ; Jiangchuan Liu…
• 关键词：Mesh ; based motion estimation ; Mobile video compression ; Motion estimation with cloud
• 刊名：Telecommunication Systems
• 出版年：2015
• 出版时间：September 2015
• 年：2015
• 卷：60
• 期：1
• 页码：85-94
• 全文大小：987 KB
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  27.Wang, Y., & L
• 作者单位：Yuan Zhao (1)
  Lei Zhang (1)
  Xiaoqiang Ma (1)
  Jiangchuan Liu (1)
  Hongbo Jiang (2)
  
  1. School of Computing Science, Simon Fraser University, 8888 University Dr, Burnaby, BC, V5A 1S6, Canada
  2. School of Computer Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Rd, Hongshan, Wuhan, Hubei, China
  
• 刊物类别：Business and Economics
• 刊物主题：Economics
  Business Information Systems
  Computer Communication Networks
  Artificial Intelligence and Robotics
  Probability Theory and Stochastic Processes
  
• 出版者：Springer Netherlands
• ISSN：1572-9451

文摘

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.