基于OpenStack云平台的计算资源动态调度及管理
发布时间：2018-11-03 06:57
【摘要】：云计算是新一代IT模式,它从网格计算,并行计算和分布式计算发展而来,用户可以使用它来方便地按需通过网络访问一个可配置的计算资源(如计算、网络、存储、应用和服务等)的共享池,只需最小化的管理工作量或服务提供商干预就可以快速地开通和释放资源。当前云环境中的资源都是通过虚拟化技术将底层的硬件资源进行虚拟化,形成一个庞大的虚拟资源池之后然后通过动态伸缩的部署方式以服务的形式提供给用户。随着使用云计算的用户持续的增加,云数据中心的规模也不断的加大,如何让使云中的虚拟化资源高效的利用并快速的提供给用户,减少用户等待时间同时提高整个云数据中心的利用率,这已经成为目前云计算环境中虚拟机资源动态调度的重要问题。 本文主要研究云数据中心虚拟化资源的动态调度策略,在总结前人工作的基础之上,基于当前最热门的开源云计算平台OpenStack展开以下一系列工作和创新之处： (1)分析了当前云计算的基本特征、体系架构和关键技术,对比了几种开源的云计算平台,同时对云数据中心的资源调度和管理的需求和关键技术进行详细的研究。 (2)基于OpenStack的架构对虚拟化资源进行建模,从服务层面和资源层面分别对资源进行描述,并提出面向计算资源实时监测反馈综合负载均衡调度策略和算法,分别以CPU、内存、存储和网络带宽四个维度对云平台的计算资源进行综合负载均值分析,同时分别计算出云平台的数据中心和物理服务器的不均衡度。通过在cloudsim仿真平台对本算法与轮转调度算法、OpenStack调度算法以及随机选择算法进行对比实验,结果表明本文提出的算法能够使申请的虚拟机实例获得更佳的部署位置,能够使云数据中心的资源达到更加的负载均衡,证明了本算法的有效性和稳定性。 (3)结合集群管理工具xCAT并对其进行二次开发了在OpenStack环境下的资源自动化管理平台,能够有效的对资源进行监控管理,并能以自动化的方式动态扩展云环境下的资源,实现规模化的自动化运维以及裸机部署管理。
[Abstract]:Cloud computing is a new generation of IT model, which is developed from grid computing, parallel computing and distributed computing. It can be used by users to easily access a configurable computing resource (such as computing, network, storage, etc.) via the network on demand. The shared pool of applications, services, etc., can be quickly opened and released with minimal management effort or service provider intervention. At present, the resources in the cloud environment are virtualized by virtualization technology, forming a huge virtual resource pool, and then providing the users with services through dynamic scalable deployment. With the continuous increase in the number of users using cloud computing, the scale of cloud data centers is also increasing. How to make the virtualization resources in the cloud efficient and quickly available to users, Reducing the waiting time of users and improving the utilization of the whole cloud data center has become an important issue of dynamic scheduling of virtual machine resources in cloud computing environment. This paper mainly studies the dynamic scheduling strategy of cloud data center virtualization resources. Based on the most popular open source cloud computing platform OpenStack, the following works and innovations are carried out: (1) the basic characteristics, architecture and key technologies of current cloud computing are analyzed, and several open source cloud computing platforms are compared. At the same time, the requirements and key technologies of resource scheduling and management in cloud data center are studied in detail. (2) based on the architecture of OpenStack, the virtual resources are modeled, the resources are described from the service level and the resource level, and a real-time monitoring feedback comprehensive load balancing scheduling strategy and algorithm for computing resources are proposed, respectively, using CPU, memory. The four dimensions of storage and network bandwidth are used to analyze the average load of computing resources of cloud platform. At the same time, the unbalance of data center and physical server of cloud platform are calculated respectively. By comparing the algorithm with rotation scheduling algorithm, OpenStack scheduling algorithm and random selection algorithm on the cloudsim simulation platform, the results show that the proposed algorithm can obtain a better deployment location for the applied virtual machine instance. It can make the resources of the cloud data center achieve more load balance, which proves the validity and stability of the algorithm. (3) combined with cluster management tool xCAT and secondary development of resource automation management platform in OpenStack environment, it can effectively monitor and manage resources, and can dynamically expand resources in cloud environment in an automatic way. Realize the automatic operation and maintenance of scale and the deployment management of naked machine.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP308
本文编号：2307038
[Abstract]:Cloud computing is a new generation of IT model, which is developed from grid computing, parallel computing and distributed computing. It can be used by users to easily access a configurable computing resource (such as computing, network, storage, etc.) via the network on demand. The shared pool of applications, services, etc., can be quickly opened and released with minimal management effort or service provider intervention. At present, the resources in the cloud environment are virtualized by virtualization technology, forming a huge virtual resource pool, and then providing the users with services through dynamic scalable deployment. With the continuous increase in the number of users using cloud computing, the scale of cloud data centers is also increasing. How to make the virtualization resources in the cloud efficient and quickly available to users, Reducing the waiting time of users and improving the utilization of the whole cloud data center has become an important issue of dynamic scheduling of virtual machine resources in cloud computing environment. This paper mainly studies the dynamic scheduling strategy of cloud data center virtualization resources. Based on the most popular open source cloud computing platform OpenStack, the following works and innovations are carried out: (1) the basic characteristics, architecture and key technologies of current cloud computing are analyzed, and several open source cloud computing platforms are compared. At the same time, the requirements and key technologies of resource scheduling and management in cloud data center are studied in detail. (2) based on the architecture of OpenStack, the virtual resources are modeled, the resources are described from the service level and the resource level, and a real-time monitoring feedback comprehensive load balancing scheduling strategy and algorithm for computing resources are proposed, respectively, using CPU, memory. The four dimensions of storage and network bandwidth are used to analyze the average load of computing resources of cloud platform. At the same time, the unbalance of data center and physical server of cloud platform are calculated respectively. By comparing the algorithm with rotation scheduling algorithm, OpenStack scheduling algorithm and random selection algorithm on the cloudsim simulation platform, the results show that the proposed algorithm can obtain a better deployment location for the applied virtual machine instance. It can make the resources of the cloud data center achieve more load balance, which proves the validity and stability of the algorithm. (3) combined with cluster management tool xCAT and secondary development of resource automation management platform in OpenStack environment, it can effectively monitor and manage resources, and can dynamically expand resources in cloud environment in an automatic way. Realize the automatic operation and maintenance of scale and the deployment management of naked machine.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP308
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