Resource Provisioning in IaaS Clouds; Auto-Scale RAM memory issue

Zolfaghar Salmanian, Habib Izadkhah, A. Isazadeh
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Abstract

In the Infrastructure-as-a-Service model of the cloud computing paradigm, virtual machines are deployed on bare-metal servers called hosts. The host is responsible for the allocation of required resources such as CPU, RAM memory, and network bandwidth for the virtual machine. Thus, the problem of resource allocation reduces to how to place the virtual machines on physical hosts. In this paper, we propose CTMC modeling based on the birth-death process of the queueing systems for the performance of the data center. We will focus on RAM allocation for virtual machines. In this architecture, a job is defined as RAM assignment for a virtual machine. Job arrivals and their service times are assumed to be based on the Poisson process and exponential distribution, respectively. The purpose of this modeling is to keep the number of running hosts minimal in a scalable datacenter while the quality of service in terms of response time is acceptable due to system utilization.
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IaaS云中的资源配置自动缩放RAM内存问题
在云计算范式的基础设施即服务模型中,虚拟机部署在称为主机的裸机服务器上。主机负责分配虚拟机所需的资源,如CPU、RAM、网络带宽等。因此,资源分配问题减少到如何将虚拟机放置在物理主机上。本文提出了基于排队系统生灭过程的CTMC模型,以提高数据中心的性能。我们将重点讨论虚拟机的RAM分配。在这个体系结构中,作业被定义为虚拟机的RAM分配。假设工作到达和服务时间分别基于泊松过程和指数分布。此建模的目的是在可伸缩数据中心中保持运行主机的数量最少,同时由于系统利用率,响应时间方面的服务质量是可接受的。
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