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Scalable video object coding & qos control for next generation space internet

Science in China(Series F) 2008年第5期51卷 599-608页

作者： TU GuoFang ZHANG Can HEINRICH Nimann XU Jie WU WeiRen School of Information Science and Engineering Graduate University of Chinese Academy of Sciences Beijing 100049 China State Key Laboratory of Information Security Graduate University of Chinese Academy of Sciences Beijing 100049 China University of Erlangen-Nuremerg Erlangen Martenssstr.3 D-91058 Erlangen Germany

The next generation space internet （NGSI） is based on all-IP-based mobile network that merges land-based network, sea-based network, sky-based network, spacebased network, deep space-based network together using existing assess network technologies. There are high signal propagation delays, high error rate, bandwidth variation and time-variety in NGSh In order to adapt to various space communication environment constraints and bandwidth variation, we propose a reduced dimension scalable video coding scheme based on CCSDS IDCS algorithm and quality of service （qos） control method by cross layer design （CLD）. The experimental result shows that this new method has better performance than that of existing algorithms, and can be adaptive to the bandwidth variation dynamically.

关键词： qos control CLD wavelet fractal interpolation reduced dimension video coding

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A Reinforcement Learning based Self-optimizing qos controller Framework for Distributed Services

A Reinforcement Learning based Self-optimizing QoS Controlle...

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2010 Chinese control and Decision Conference

作者： David Levy School of Electric and Information Engineering University of Sydney

＜正＞qos control is complicated by limited knowledge of system characteristics and continuous evolving features in modern distributed *** this paper,we propose a practical reinforcement learning based self-optimized qos controller algorithm with the ability to guarantee differentiated average response time requirements for different service *** proposed solution consists of two key contributions:the reinforcement learning based self-optimizing control algorithm and full evaluations of this control *** on the prototype show that standard reinforcement learning can learn and self- optimize the control knowledge efficiently in feasible training time with only partial system knowledge.

关键词： qos control Self-optimizing Reinforcement Learning

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A point-based rendering approach for real-time interaction on mobile devices

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Science in China(Series F) 2009年第8期52卷 1335-1345页

作者： LIANG XiaoHui ZHAO QinPing HE ZhiYing XIE Ke LIU YuBo State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Technology Beihang UniversityBeijing 100191 China

Mobile device is an important interactive platform. Due to the limitation of computation, memory, display area and energy, how to realize the efficient and real-time interaction of 3D models based on mobile devices is an important research topic. Considering features of mobile devices, this paper adopts remote rendering mode and point models, and then, proposes a transmission and rendering approach that could interact in real time. First, improved simplification algorithm based on MLS and display resolution of mobile devices is proposed. Then, a hierarchy selection of point models and a qos transmission control strategy are given based on interest area of operator, interest degree of object in the virtual environment and rendering error. They can save the energy consumption. Finally, the rendering and interaction of point models are completed on mobile devices. The experiments show that our method is efficient.

关键词： virtual environment mobile devices point models simplification qos control area of interest interest degree

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