虚拟化系统资源重组方法研究
发布时间：2018-10-18 07:14
【摘要】：云计算作为效用计算，并行计算，网格计算等计算模式融合的产物，它通过资源池化的方式，弹性的对外提供计算、存储以及网络服务。但日益膨胀的大规模云计算数据中心导致了管理困难以及运营成本攀升的窘境，具体表现在：资源利用率仍旧不高，能耗惊人，虚拟机资源分配不合理。具有弹性特征的云计算资源管理主要考虑两方面的因素：用户QoS以及云服务提供商收入。多数虚拟机用户仍然按峰值需求预定虚拟机的资源配置，导致多数时段的资源闲置，服务器长时间空载运行，浪费了大量的电力能源。学术界诸多文献针对资源利用率问题提出了面向虚拟机集群的资源分配以及部署方法，而既满足用户QoS又不浪费过多资源的虚拟机最佳资源配置与负载类型及强度息息相关，本文针对以往多数文献对单个虚拟机最佳资源配置与负载关系研究的不足之处展开理论以及实验分析，并结合博弈论应用于有限资源条件下对不同资源偏好的虚拟机资源重组优化问题中。 主要工作总结如下： 1)基于虚拟机web服务场景，使用排队模型针对web服务请求的平均请求速率、平均服务时间、资源平均利用率、平均响应时间等性能指标建模，并结合经典排队论Little公式推导出了平均响应时间与平均请求速率，平均服务时间的关系；通过T时间内的web服务运行过程观察数据，包括资源利用率，平均响应时间以及平均请求速率，对模型进行了一致性检验，计算出web请求的平均服务时间；在八组以负载强度为控制变量的实验测试中，得到与负载强度相应的虚拟机资源临界点，当虚拟机资源配置低于临界点，响应时间出现急剧上升，最后通过对实验数据的回归分析得出了服务请求速率与最佳资源配置的显著关系。 2)针对有限资源条件下的虚拟机资源重组问题，根据虚拟机最佳资源配置决策是否冲突分别提出了解决方法。基于上述性能模型，，虚拟机根据部署的负载类型与强度独立计算申请所需资源，若虚拟机目标资源配置总和未超过初始重组资源总和，则直接根据各自需要进行资源重分配，否则认为资源重组冲突，针对冲突问题，应用博弈谈判，经过离散迭代求解。实验证明了该方法在以下几点的有效性：提高资源利用率，优化虚拟机性能，保障资源重分配的公平性。
[Abstract]:Cloud computing is the product of utility computing, parallel computing, grid computing and so on. It provides computing, storage and network services through resource pool. However, the expanding large-scale cloud computing data center has led to the difficulties of management and rising operating costs, which are reflected in: the resource utilization is still not high, the energy consumption is amazing, and the allocation of virtual machine resources is unreasonable. Flexible cloud computing resource management mainly considers two factors: user QoS and cloud service provider revenue. Most virtual machine users still preorder the resource allocation of virtual machine according to the peak demand, which leads to idle resources in most periods, the server running without load for a long time, and wasting a lot of power energy. For the resource utilization problem, many literatures have put forward the resource allocation and deployment method for virtual machine cluster. However, the optimal allocation of virtual machine resources, which not only satisfies the user QoS but also does not waste too much resources, is closely related to the load type and intensity. In this paper, the theoretical and experimental analysis is carried out in view of the shortcomings of most previous literatures on the relationship between optimal resource allocation and load of a single virtual machine. And the game theory is used to optimize the resource recombination of virtual machine with different resource preference under the condition of limited resources. The main work is summarized as follows: 1) based on the virtual machine web service scenario, the average request rate, average service time, average resource utilization and average response time of web service requests are modeled by queuing model. The relationship between average response time, average request rate and average service time is derived by using the classical queuing theory Little formula, and the data of web service running process in T time, including resource utilization, are observed. The average response time and the average request rate were tested to calculate the average service time of the web request, and in eight groups of experiments with load intensity as the control variable, the average service time of the web request was calculated. The critical point of virtual machine resources corresponding to the load intensity is obtained. When the virtual machine resource allocation is below the critical point, the response time increases sharply. Finally, through regression analysis of experimental data, the significant relationship between service request rate and optimal resource allocation is obtained. 2) aiming at the problem of virtual machine resource reorganization under limited resources, According to the optimal resource allocation decision of virtual machine, the solutions are proposed respectively. Based on the above performance model, the virtual machine independently calculates the required resources according to the load type and intensity of the deployment. If the total allocation of the target resources of the virtual machine is not more than the sum of the initial reorganization resources, then the resources are reallocated directly according to their respective needs. Otherwise, it is considered that the conflict of resource recombination is solved by using game negotiation and discrete iteration to solve the conflict problem. Experiments show that the proposed method is effective in the following aspects: improving resource utilization, optimizing the performance of virtual machine and ensuring the fairness of resource redistribution.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.01
本文编号：2278387
[Abstract]:Cloud computing is the product of utility computing, parallel computing, grid computing and so on. It provides computing, storage and network services through resource pool. However, the expanding large-scale cloud computing data center has led to the difficulties of management and rising operating costs, which are reflected in: the resource utilization is still not high, the energy consumption is amazing, and the allocation of virtual machine resources is unreasonable. Flexible cloud computing resource management mainly considers two factors: user QoS and cloud service provider revenue. Most virtual machine users still preorder the resource allocation of virtual machine according to the peak demand, which leads to idle resources in most periods, the server running without load for a long time, and wasting a lot of power energy. For the resource utilization problem, many literatures have put forward the resource allocation and deployment method for virtual machine cluster. However, the optimal allocation of virtual machine resources, which not only satisfies the user QoS but also does not waste too much resources, is closely related to the load type and intensity. In this paper, the theoretical and experimental analysis is carried out in view of the shortcomings of most previous literatures on the relationship between optimal resource allocation and load of a single virtual machine. And the game theory is used to optimize the resource recombination of virtual machine with different resource preference under the condition of limited resources. The main work is summarized as follows: 1) based on the virtual machine web service scenario, the average request rate, average service time, average resource utilization and average response time of web service requests are modeled by queuing model. The relationship between average response time, average request rate and average service time is derived by using the classical queuing theory Little formula, and the data of web service running process in T time, including resource utilization, are observed. The average response time and the average request rate were tested to calculate the average service time of the web request, and in eight groups of experiments with load intensity as the control variable, the average service time of the web request was calculated. The critical point of virtual machine resources corresponding to the load intensity is obtained. When the virtual machine resource allocation is below the critical point, the response time increases sharply. Finally, through regression analysis of experimental data, the significant relationship between service request rate and optimal resource allocation is obtained. 2) aiming at the problem of virtual machine resource reorganization under limited resources, According to the optimal resource allocation decision of virtual machine, the solutions are proposed respectively. Based on the above performance model, the virtual machine independently calculates the required resources according to the load type and intensity of the deployment. If the total allocation of the target resources of the virtual machine is not more than the sum of the initial reorganization resources, then the resources are reallocated directly according to their respective needs. Otherwise, it is considered that the conflict of resource recombination is solved by using game negotiation and discrete iteration to solve the conflict problem. Experiments show that the proposed method is effective in the following aspects: improving resource utilization, optimizing the performance of virtual machine and ensuring the fairness of resource redistribution.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.01
【参考文献】
相关期刊论文 前2条
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2 周文俊;曹健;;基于预测及蚁群算法的云计算资源调度策略[J];计算机仿真;2012年09期
本文编号：2278387
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