CSR: Small: PROM in Clouds: Exploiting Scheduling for PeRformance OptiMization in Clouds

云计算正在成为一种有吸引力的计算模式，可以从云提供商那里租用硬件和软件资源，以实现更好的规模经济、弹性、可用性和灵活性，以满足大量服务的需求。设计此类云平台的一个主要挑战是如何提供高且可预测的性能以及服务质量(Qos)保证。性能不可预测性是由系统规模、工作负载动态性、虚拟化开销、资源共享和争用等多种因素造成的。该方案的目的是通过三个相互交织的任务来研究云环境中的性能增强和性能量化技术。首先，将开发一个由高级作业调度器和细粒度资源管理器组成的综合调度框架，以有效地管理云资源以提高性能。其次，将开发性能预测模型来估计云平台中的作业完成时间(JCT)。第三，为了提供服务质量保证，将所提出的调度器和分析模型相结合，建立控制理论模型。我们将使用MapReduce和其他典型的云工作负载在真实平台上的测量结果来验证所提出的想法。这项研究解决了云计算的一个主要问题--如果我的应用程序被移动到语音上，会对性能产生什么影响？如果成功回答了这个问题，它将对支持云的应用程序领域产生巨大的影响。这项工作的交叉性质可以培养新的研究途径。除了在建筑、分布式系统和性能建模等领域的本科生和研究生培训外，将特别关注让女性和少数族裔学生参与这一项目。这项研究中开发的建模工具和技术将公开提供。

Cloud computing is emerging as an attractive computing paradigm, whereboth hardware and software resources can be leased from a cloudprovider to achieve better economy of scale, elasticity, availability,and flexibility for a plethora of services. A major challenge indesigning such cloud platforms is in providing high and predictableperformance along with Quality of Service (QoS) guarantees. Theperformance unpredictability is attributed to a myriad of factorsincluding system scale, workload dynamism, virtualization overheads,resource sharing and contention.The objective of this proposal is to investigate performanceenhancement and performance quantification techniques in a cloudenvironment through three intertwined tasks.First, a comprehensive scheduling framework consisting of a high-leveljob scheduler and a fine-grained resource manager will be developedfor efficient management of cloud resources for performance enhancement.Second, performance prediction models will be developed for estimatingjob completion time (JCT) in a cloud platform.Third, for providing QoS guarantees, a control-theoretic modelincorporating the proposed scheduler and analytical models will bedeveloped. Measurements on real platforms with MapReduce and other representative cloud workloads will be used to validate theproposed ideas.This research addresses one of the main concerns of cloud computing -What are the performance implications if my application is moved to acloud? If successful in answering this question, it would have a tremendousimpact on the cloud-enabled application domains. The cross-cuttingnature of this work can foster new research avenues.In addition to undergraduate and graduate student training in areassuch as architecture, distributed systems, and performance modeling,special attention will be given to involving women and minoritystudents in this project. The modeling tools and techniques developedin this research will be made publicly available.