云数据中心并行计算模型与作业调度研究

项目名称： 云数据中心并行计算模型与作业调度研究

项目编号： No.61202041

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 计算机科学学科

项目作者： 曹海军

作者单位： 西安交通大学

项目金额： 26万元

中文摘要： 云计算平台的作业执行子系统主要负责计算模型、资源分配与作业调度。目前，云计算环境下的作业执行正面临着新的机遇与挑战，例如，单集群节点通常采用了多处理器混合架构；多个计算模型(MapReduce、DAG、Stream)和多种作业类型(系统作业、用户交互式作业、实时作业等)并存。因此，如何根据计算模型，调度不同类型作业到异构复杂的集群计算资源上执行成为云计算系统平台面临的关键科学问题。为了提高作业调度与执行效率，本项目将综合分析计算资源、计算模型、作业三者特点，从以下三个层面开展研究：(1)面向多处理器集群系统的作业调度；(2)面向异构集群计算资源的作业调度研究；(3)面向流数据处理的计算模型与作业执行优化。本项目的研究成果将可以直接应用于真实的云计算系统平台，支持多个计算模型和作业类型，能够提高作业执行子系统的吞吐率、资源利用率、公平性，减少单个作业完成时间。

中文关键词： 云计算；并行计算模型；作业调度；虚拟化；

英文摘要： In general, the job execution subsystem of cloud computing platform mainly involves computing model, resource management, and job scheduling. Currently, some new opportunities and challenges have been posed for job execution in cloud data center,for instance, 1)the cluster node tends to be equipped with multiple processors and of hybrid architecture; 2)several computing models coexist, such as MapReduce, DAG, and Stream; and 3)jobs can be classified into several types, e.g., system job, user-submitted interactive job，realtime job. Therefore, according to the computing model, how to schedule a number of jobs with different types to the heterogeous cluster nodes becomes essential.To improve the efficiency of parallel job scheduling and execution, taking features of computing resources, computing model and parallel job into consideration, this project aims to do research on three aspects: (1)job scheduling in the cluster system with hybrid multi-processor node;(2)job scheduling in heterogeous cluster; and (3) computating model for online data-stream processing and job execution runtime optimization. Overall, the achievements of this project can be applied into the real cloud computing platform. In addition, it would support several types of computing model and job, as well as improving the cloud job execution subsy

英文关键词： Cloud Computing；Parallel Computing Model；Job Scheduling；Virtualization；