CSR--EHS: Dynamic Resource Management for Multimedia Applications on Embedded Systems

CSR--EHS：嵌入式系统多媒体应用的动态资源管理

• 批准号: 0509522
• 负责人: Mihaela van der Schaar
• 金额: $ 27万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-15 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0509522&HistoricalAwards=false
• 关键词: CSR; EHS; Dynamic; Resource; Management

Existing approaches to implementing multimedia encoding and decoding algorithms on embedded systems have several drawbacks. First, multimedia algorithms are designed without explicitly taking resource constraints into account. Second, current embedded systems often assume "worst-case" resource utilization for the design and implementation of compression techniques, thereby neglecting the fact that multimedia algorithms require time-varying resources. Third, the algorithms and their implementation are not jointly optimized, resulting in sub-optimal performance. Finally, existing adaptive systems for multimedia are, at best, reactive, i.e., they adapt their resources to past data inputs, instead of modeling and predicting future resource requirements and planning accordingly. In this project, the abovementioned limitations are addressed to improve the efficiency of multimedia applications on embedded systems. Specifically, this research investigates dynamic resource planning techniques that can jointly optimize the complexity of the multimedia algorithms and the resource utilization, while meeting a given system constraint. This forms the basis for proactive resource management by using feed-forward control mechanisms like stochastic modeling, learning and forecasting. Finally, rate- and complexity-scalable compression schemes are necessary to enable optimized adaptation to available resources. Developing such an integrated application-implementation framework is of fundamental importance, since it not only leads to improved multimedia performance over existing embedded systems, but also provides valuable insights into the design of next generation multimedia compression algorithms that should be complexity scalable, as well as embedded systems designs that should be multimedia aware.The broader impact is in the area of educating next generation students and industry partners in resource-aware system design, which is critical to realize the vision of ubiquitous and autonomous computing systems of the future.

在嵌入式系统上实现多媒体编码和解码算法的现有方法具有若干缺点。首先，多媒体算法的设计没有明确考虑资源约束。其次，目前的嵌入式系统往往假设“最坏情况下”的压缩技术的设计和实施的资源利用率，从而忽略了多媒体算法需要时变资源的事实。第三，算法及其实现没有联合优化，导致次优性能。最后，现有的多媒体自适应系统充其量是反应性的，即，它们根据过去的数据输入调整其资源，而不是建立模型和预测未来的资源需求并相应地进行规划。在本计画中，针对上述限制，以提高多媒体应用在嵌入式系统上的效率。具体而言，本研究探讨动态资源规划技术，可以共同优化的多媒体算法的复杂性和资源利用率，同时满足给定的系统约束。这构成了通过使用前馈控制机制（如随机建模、学习和预测）进行主动资源管理的基础。最后，速率和复杂度可伸缩的压缩方案是必要的，以实现优化的适应可用资源。开发这样一个集成的应用程序实现框架具有根本的重要性，因为它不仅导致在现有的嵌入式系统上改进多媒体性能，而且还为设计下一代多媒体压缩算法提供了有价值的见解，这些算法应该是复杂度可伸缩的，以及嵌入式系统设计，应该是多媒体感知。更广泛的影响是在教育下一代学生和行业合作伙伴的领域在资源感知系统设计，这是至关重要的，以实现无处不在的和自治的计算系统的未来的愿景。