Complexity Optimization Strategies for Adaptive Multimedia Receivers

自适应多媒体接收器的复杂度优化策略

• 批准号: 0541453
• 负责人: Mihaela van der Schaar
• 金额: $ 49.96万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-15 至 2010-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0541453&HistoricalAwards=false
• 关键词: Complexity; Optimization; Strategies; Adaptive; Multimedia

This project is premised on the belief that a fundamentally different approach is necessary for designing and implementing multimedia compression, protection and transmission algorithms and systems for resource-constrained networked devices. The main idea is that instead of considering multimedia algorithms as a given and adapting the implementations reactively to match the requirements of these algorithms, proactive joint optimization of the algorithms, their parameters, and the implementation task partitioning is performed. The system is therefore able to maintain operation at a point in rate-distortion-complexity space in accordance with a constellation of factors and constraints including distortion tolerance, power, platform architecture characteristics, network behavior, and critically, data attributes. A global optimization framework and associated algorithms that consider the data-specific impact on the system factors listed above, allowing cost functions describing these tradeoffs to be formally described and then optimized as appropriate to different devices, networks and applications will be developed. Specifically: 1) complexity description methods and models, 2) data-aware channel decoding methods that combine feedback from the decoder and system knowledge to adapt the processing, 3) joint source-channel coding methods that exploit error concealment in combination with knowledge of the time- and content-varying sensitivity of multimedia data to errors, and 4) optimized resource management. The broader impact of the project is in the area of educating next generation students and industry partners in optimized resource-aware system design. Developing formal methods, algorithms and models will lead to improved multimedia performance over existing resource-constrained systems and also provide valuable insights into the design of next generation multimedia compression algorithms that should be complexity scalable, as well as system designs that should be multimedia aware.

该项目的前提是，对于设计和实施多媒体压缩，保护和传输算法以及用于资源约束的网络设备的系统是必不可少的方法。主要思想是，与其考虑多媒体算法为给定，并反应地调整实现以匹配这些算法的要求，而是执行算法的主动关节优化，而是执行其参数和实现任务分配。因此，该系统能够根据因素和约束，包括变形容忍，功率，平台架构特征，网络行为以及关键的数据属性，将操作维持在速率延伸 - 复杂空间的一个点。一个全球优化框架和相关算法考虑了对上述系统因素的特定数据影响，从而将描述这些权衡的成本功能进行正式描述，然后将其优化为适用于不同设备，网络和应用程序。具体：1）复杂性描述方法和模型，2）结合解码器和系统知识的反馈以适应处理的数据感知通道解码方法，3）联合源通道编码方法，将错误隐藏与知识相结合的知识与知识相结合多媒体数据对错误的时间和内容相反的敏感性，以及4）优化资源管理。该项目的更广泛影响是在优化的资源感知系统设计方面教育下一代学生和行业合作伙伴。开发正式的方法，算法和模型将导致对现有资源受限系统的多媒体性能的改善，并为下一代多媒体压缩算法的设计提供宝贵的见解，这些算法应该是可扩展性的复杂性，以及应该对多媒体的系统设计。