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Modeling and Simulation of Scalable Cloud Computing Environments and the CloudSim Toolkit: Challenges and Opportunities

可扩展的云计算环境下的仿真与建模：挑战与机遇CloudSim工具包

Rajkumar Buyya1, Rajiv Ranjan2 and Rodrigo N. Calheiros1,3

1 Grid Computing and Distributed Systems (GRIDS) Laboratory Department of Computer Science and Software Engineering The University of Melbourne, Australia 2 Department of Computer Science and Engineering The University of New South Wales, Sydney, Australia 3Pontifical Catholic University of Rio Grande do Sul Porto Alegre, Brazil Email: {raj, rodrigoc}@csse.unimelb.edu.au, rajiv@unsw.edu.au

Abstract

概括

Cloud computing aims to power the next generation data centers and enables application service providers to lease data center capabilities for deploying applications depending on user QoS (Quality of Service) requirements. Cloud applications have different composition, configuration, and deployment requirements. Quantifying the performance of resource allocation policies and application scheduling algorithms at finer details in Cloud computing environments for different application and service models under varying load, energy performance (power consumption, heat dissipation), and system size is a challenging problem to tackle. To simplify this process, in this paper we propose CloudSim: an extensible simulation toolkit that enables modelling and simulation of Cloud computing environments. The CloudSim toolkit supports modelling and creation of one or more virtual machines (VMs) on a simulated node of a Data Center, jobs, and their mapping to suitable VMs. It also allows simulation of multiple Data Centers to enable a study on federation and associated policies for migration of VMs for reliability and automatic scaling of applications.

云计算的目的是为下一代数据中心提供动力，使应用服务提供商能够根据用户QoS（服务质量）需求来租用数据中心的能力来部署应用程序。云应用程序具有不同的组成、配置和部署需求。在云计算环境下，针对不同应用和服务模型在不同负载下的资源分配策略和应用调度算法的性能进行量化，能量性能（功耗、散热）和系统规模是一个具有挑战性的问题。为了简化这个过程，本文提出了一种可扩展的模型：仿真工具包，使云计算环境的仿真建模。CloudSim工具包支持与一个或多个虚拟机（VM）模型的建立在一个模拟的节点数据中心工作，及其映射到合适的虚拟机。它还允许对多个数据中心进行模拟，以便研究联合和相关的迁移策略，以提高应用程序的可靠性和自动伸缩性。

Introduction

简介

software as services, which are made available as subscription-based services in a pay-as-you-go model to consumers. These services in industry are respectively referred to as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). The importance of these services is highlighted in a recent report from Berkeley as: “Cloud computing, the long-held dream of computing as a utility, has the potential to transform a large part of the IT industry, making software even more attractive as a service” 【11】

云计算将基础设施、平台和软件作为服务提供，这些服务可以作为按需付费的服务提供给消费者。这些服务行业分别称为基础设施即服务（IaaS）、平台即服务（PaaS），和软件即服务（SaaS）。伯克利在最近的一份报告中强调了这些服务的重要性：“云计算作为一种实用的计算机长期以来的梦想，有潜力改变IT行业的大部分，使软件作为服务更具吸引力”。【11】

Clouds 【10】 aim to power the next generation data centers by exposing them as a network of virtual services

(hardware, database, user-interface, application logic) so that users are able to access and deploy applications from anywhere in the world on demand at competitive costs depending on users QoS (Quality of Service) requirements 【1】. Developers with innovative ideas for new Internet services are no longer required to make large capital outlays in the hardware and software infrastructures to deploy their services or human expense to operate it 【11】. It offers significant benefit to IT companies by freeing them from the low level task of setting up basic hardware and software infrastructures and thus enabling more focus on innovation and creation of business values.

云【10】旨在将下一代数据中心作为虚拟服务网络暴露出来，为下一代数据中心提供动力。 （硬件、数据库、用户界面、应用程序逻辑）使用户能够根据需要根据用户QoS（服务质量）需求在竞争的成本下访问和部署来自世界任何地方的应用程序【1】。对于新的因特网服务具有创新思想的开发者不再需要在硬件和软件基础设施上投入大量资金来部署他们的服务或人力来操作它【11】。它使IT公司从建立基本硬件和软件基础设施的低级别任务中获益，从而使更多地专注于创新和创造业务价值，从而为IT公司带来了巨大的好处。

Some of the traditional and emerging Cloud-based applications include social networking, web hosting, content delivery, and real time instrumented data processing. Each of these application types has different composition, configuration, and deployment requirements. Quantifying the performance of scheduling and allocation policies in a real Cloud environment for different application and service models under different conditions is extremely challenging because: (i) Clouds exhibit varying demand, supply patterns, and system size; and (ii) users have heterogeneous and competing QoS requirements. The use of real infrastructures such as Amazon EC2, limits the experiments to the scale of the infrastructure, and makes the reproduction of results an extremely difficult undertaking. The main reason for this being the conditions prevailing in the Internet-based environments are beyond the control of developers of resource allocation and application scheduling algorithms.

一些传统的和新兴的基于云的应用程序包括社交网络、Web主机、内容传递和实时仪表数据处理。每个应用程序类型都有不同的组成、配置和部署需求。在不同的应用程序和服务模型中，在不同的条件下量化调度和分配策略在实际云环境中的性能是非常具有挑战性的，因为：（1）云表现出不同的需求、供应模式和系统大小；（2）用户具有异构的和竞争性的QoS要求。真正的基础设施如亚马逊EC2的使用，限制了基础设施的规模的实验，进行了一项艰巨的任务，结果的再现。造成这种情况的主要原因是，基于Internet的环境超出了资源分配和应用程序调度算法开发人员的控制范围。

An alternative is the utilization of simulation tools that open the possibility of evaluating the hypothesis prior to software development in an environment where one can reproduce tests. Specifically in the case of Cloud computing, where access to the infrastructure incurs payments in real currency, simulation-based approaches offer significant benefits to Cloud customers by allowing them to: (i) test their services in repeatable and controllable environment free of cost; and (ii) tune the performance bottlenecks before deploying on real Clouds. At the provider side, simulation environments allow evaluation of different kinds of resource leasing scenarios under varying load and pricing distributions. Such studies could aid providers in optimizing the resource access cost w

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