CSR: Small: Resource Management for Real-time Cloud Computing

云计算支持灵活、动态的外包，同时提高成本效率。然而，由于当前云基础设施缺乏及时性支持，这些运营和经济效益目前无法用于安全关键型和任务关键型实时应用程序。在云平台上提供实时保证面临着一些新的挑战，因为云平台不是为响应时间保证而设计的，而是为了实现弹性和按需提供丰富资源的假象。本研究通过资源管理技术扩展了当前的云基础设施，以实现云上的实时保证。建议的工作重点是将数据密集型实时应用程序调度到云资源上，以满足其时间要求。该项目(i)提出了一个正式的框架，用于云环境中实时应用的建模和性能评估，重点是数据并行中间件；（ii）开发用于在线设置中调度实时云应用程序连续流的算法；（iii）基于概率模型、分层调度技术、多模式技术和反馈控制技术，设计技术来解决由虚拟化和机器故障引入的问题；(v)在实际实时应用的背景下评估这些技术。该研究将通过增强现有的开源平台，开发出至少一种数据并行中间件基础设施的实时变体。研究原型将作为开源发布，以刺激针对实时应用和系统的云计算的研究和开发。在这个项目中开发的研究概念和工具将被纳入宾夕法尼亚大学的相关课程。

Cloud computing enables flexible, dynamic outsourcing while improving cost efficiencies. These operational and economic benefits, however, are today not available to safety-critical and mission-critical real-time applications due to the lack of timeliness supports by current cloud infrastructures. Providing real-time guarantees on cloud platforms faces several novel challenges because cloud platforms are not designed for response time guarantees but to achieve elasticity and the illusion of abundant resources available on demand.This research extends current cloud infrastructures with resource management techniques to enable real-time guarantees on the cloud. The proposed work focuses on the scheduling of data-intensive real-time applications onto cloud resources to meet their timing requirements. The project (i) proposes a formal framework for modeling and performance evaluation of real-time applications in cloud environments, with a focus on data-parallel middleware; (ii) develops algorithms for scheduling continuous streams of real-time cloud applications in an online setting; (iii) designs techniques to address issues introduced by virtualization and machine failures based on probabilistic models, hierarchical scheduling techniques, multi-mode techniques, and feedback control techniques; and (v) evaluates these techniques in the context of practical real-time applications. The research will result in the development of a real-time variant of at least one data-parallel middleware infrastructure by enhancing existing open-source platforms. Research prototypes will be released as open source to spur the research and development of cloud computing targeting real-time applications and systems. Research concepts and tools developed in this project will be incorporated into relevant courses at Penn.