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Adriano Vogel Surveying the Robustness and Analyzing the Performance Impact of Open Source Infrastructure As a Service Managemen

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Adriano Vogel Surveying the Robustness and Analyzing the Performance Impact of Open Source Infrastructure As a Service Managemen ADRIANO VOGEL SURVEYING THE ROBUSTNESS AND ANALYZING THE PERFORMANCE IMPACT OF OPEN SOURCE INFRASTRUCTURE AS A SERVICE MANAGEMENT TOOLS Três de Maio 2015 ADRIANO VOGEL SURVEYING THE ROBUSTNESS AND ANALYZING THE PERFORMANCE IMPACT OF OPEN SOURCE INFRASTRUCTURE AS A SERVICE MANAGEMENT TOOLS Undergraduate Thesis Sociedade Educacional Três de Maio Faculdade Três de Maio Curso de Tecnologia em Redes de Computadores Advisor: M. Sc. Dalvan Griebler Três de Maio 2015 AGRADECIMENTOS Este trabalho é dedicado a minha familia por todo o apoio e pela paciência nos momentos que estive ausente para a realização desse estudo. Um agradecimento especial ao meu orientador Dalvan Griebler, tanto pela oportunidade e confiança para esse trabalho, quanto pelo esforço da orientação e revisão da escrita. Agradeço também pela equipe do grupo de pesquisa LARCC e projeto HiPerfCloud pelo suporte e oportunidade de discussões. TERMO DE APROVAÇÃO ADRIANO VOGEL SURVEYING THE ROBUSTNESS AND ANALYZING THE PERFORMANCE IMPACT OF OPEN SOURCE INFRASTRUCTURE AS A SERVICE MANAGEMENT TOOLS Relatório aprovado como requisito parcial para obtenção do título de Tecnólogo em Redes de Computadores concedido pela Faculdade de Tecnologia em Redes de Computadores da Sociedade Educacional Três de Maio, pela seguinte Banca examinadora: Orientador: Prof. Dalvan Griebler, M.Sc. Faculdade de Tecnologia em Redes de Computadores da SETREM Drando. Fauzi de Moraes Shubeita Faculdade de Tecnologia em Redes de Computadores da SETREM M.Sc. Vinícius da Silveira Serafim Faculdade de Tecnologia em Redes de Computadores da SETREM Dr. Claudio Schepke Universidade Federal do Pampa (UNIPAMPA) - Alegrete Três de Maio, 07 de agosto de 2015. ABSTRACT Cloud computing is an alternative to offer computational resources for users link dif- ferent technologies (virtualization, grid computing, cluster and parallel processing). Firstly, public cloud providers started offering services and computational resources over the Internet. Meanwhile, the private clouds began to deploy solutions inside the corporations domain. This cloud type becomes suitable because it increases the secu- rity and flexibility and avoids a third party dependency. Currently, there are several IaaS open source cloud solutions available to build a public or private cloud. However, their robustness is still unknown as well as the performance impacts. In this thesis, the goal was to evaluate these IaaS tools, concerning the features and support for robustness (flexibility and resilience). Also, a survey state of the art for performance on a cloud was conducted to highlight cloud’s challenges and potential solutions for reducing its performance overhead. The results demonstrated that the open source cloud IaaS so- lutions can provide high robustness levels and are suitable for enterprise applications. Therefore, the most flexible IaaS tool is the CloudStack as well as the OpenStack is the most resilient. Additionally, an equation to find the reliability rates for experiments on the cloud was created due to the performance variation problem found in the survey. Keywords: Cloud Computing, Infrastructure as a Service, Survey, Perfor- mance Analysis, Computer Networks. ABSTRACT A computação em nuvem surgiu como uma alternativa para oferecer recursos com- putacionais através da utilização de tecnologias consolidadas nas últimas décadas (virtualização, computação em grade, cluster e processamento paralelo). Dessa forma, os provedores de nuvem pública surgiram oferecendo serviços e recursos computa- cionais através da internet. Ao mesmo tempo, o conceito de nuvem privada surgiu, nessa tecnologia a nuvem é implantada dentro do domínio das empresa utilizando a própria infraestrutura. Nesse estudo, as soluções para nuvens do tipo IaaS foram availiadas em relação as características e ao suporte para robustez de nuvem (flex- ibilidade e resiliência). Além disso, foi conduzida uma pesquisa do estado da arte para desempenho em nuvem buscando destacar os desafios e prováveis soluções para reduzir a degradação da performance de aplicações executadas na nuvem. Os resultados mostram que algumas soluções de código aberto para nuvem IaaS podem alcançar elevados níveis de robustez e podem ser adequadas para a execução de aplicações corporativas. Ainda, foi desenvolvida uma equação para encontrar o nível de confiabilidade de experimentos. Keywords: Computação em Nuvem, Infraestrutura como Serviço, Survey, Análise de desempenho, Redes de Computadores. LIST OF FIGURES 2.1 CPU components and interactions. 38 2.2 Memory hierarchy. 39 2.3 SISD architecture. 41 2.4 MIMD architecture. 41 2.5 Shared (left) and distributed (right) memory MIMD. 42 2.6 Types of Cloud Services. 50 2.7 3 Types of Cloud. 54 2.8 Example of load distribution. 61 2.9 Workstation Distributed System model. 62 3.1 Cloudstack architecture. 72 3.2 Cloudstack infrastructure overview. 73 3.3 Cloudstack deployment architecture overview. 74 3.4 OpenNebula infrastructure overview. 75 3.5 Eucalyptus components. 76 3.6 Eucalyptus architecture overview. 77 3.7 Nimbus deployment. 79 3.8 OpenStack overview. 80 3.9 OpenStack conceptual architecture. 80 3.10 IaaS proposed taxonomy. 85 3.11 IaaS survey flexibility scores overview. 101 3.12 IaaS survey flexibility support percentage. 101 3.13 IaaS survey resilience overall scores. 104 3.14 IaaS survey resilience percentage. 104 3.15 IaaS tools robustness. 106 3.16 Virtualization performance overhead factors. 109 3.17 IaaS overview. Adapted from Celesti et al. (2013). 119 3.18 IaaS resources provision. 120 3.19 OSv architecture. 123 3.20 Hypervisor and container virtualization. 124 LIST OF TABLES 1.1 Activities schedule. 26 1.2 Estimated costs. 27 3.1 Related Surveys. 84 3.2 IaaS survey flexibility overview. 92 3.3 IaaS survey tools flexibility(a). 94 3.4 IaaS survey tools flexibility(b). 95 3.5 IaaS tools resilience. 103 3.6 Performance variation overview. 112 LIST OF ABBREVIATIONS AND ACRONYMS API Application Programming Interface AWS Amazon Web Service COV Coefficient of Variation CRM Customer Relationship Management DHCP Dynamic Host Configuration Protocol DNS Domain Name System EC2 Elastic Compute Cloud ERP Enterprise Resource Planning GPL General Public License HPC High-performance computing IaaS Infrastructure as a Service IP Internet Protocol LAN Local Area Network LARCC Laboratory of Advanced Researches for Cloud Computing LVM Logical Volume Management LXC Linux Containers MAN Metropolitan Area Network MBW Memory Bandwidth Benchmark MIMD Multiple-Instruction, Multiple-Data MISD Multiple-Instruction, Single-Data NASA National Aeronautics and Space Administration NFS Network File System NVP Network Virtualization Platform PaaS Platform as a Service RHEL Red Hat Enterprise Linux SaaS Software as a Service SCM Supply Chain Management SETREM Sociedade Educacional Três de Maio SIMD Single-Instruction, Multiple-Data SISD Single-Instruction, Single-Data SMB Server Message Block SSH Secure Shell OS Operating System OSG Object Storage Gateways OVS OpenVSwitch QCOW QEMU Copy On Write QEMU Quick Emulator QoS Quality of Service iSCSI Internet Small Computer System Interface TCP/IP Transmission Control Protocol/Internet Protocol TFTP Trivial File Transfer Protocol VHD Virtual Hard Disk VM Virtual Machine VMDK Virtual Machine Disk VMFS Virtual Machine File System VMM Virtual Machine Monitor WAN Wide Area Network CONTENTS INTRODUCTION .................................... 15 CHAPTER1: RESEARCH PLAN ........................... 18 1.1 THEME . 18 1.1.1 Theme Delimitation ............................. 18 1.2 PROBLEM . 19 1.3 HYPOTHESES . 20 1.4 VARIABLES . 20 1.5 OBJECTIVES . 20 1.5.1 General Objective ............................. 20 1.5.2 Specific Objectives ............................. 21 1.6 JUSTIFICATION . 21 1.7 METHODOLOGY . 23 1.7.1 Methods ................................... 23 1.7.2 Procedures ................................. 25 1.7.3 Research Techniques ........................... 25 1.8 RESOURCES . 25 1.8.1 Human Resources ............................. 25 1.8.2 Material Resources ............................. 26 1.8.3 Institutional resources ........................... 26 1.9 SCHEDULE . 26 1.10 ESTIMATED COSTS . 27 CHAPTER2: LITERATURE REVIEW ........................ 28 2.1 DEFINITION OF TERMS . 28 2.1.1 Operating System ............................. 28 2.1.2 Computer Networks ............................ 28 2.1.3 Performance Evaluation .......................... 29 2.1.3.1 Response Time (Latency) .......................... 30 2.1.3.2 Throughput .................................. 31 13 2.1.3.3 Speedup ................................... 31 2.1.3.4 Efficiency ................................... 32 2.1.4 Resource Isolation ............................. 32 2.1.5 Statistical Significance .......................... 33 2.1.6 Survey .................................... 33 2.1.7 Open Source ................................ 34 2.1.8 Quality-of-Services ............................. 34 2.2 BACKGROUND . 35 2.2.1 Computer Architecture .......................... 36 2.2.2 Flynn’s Taxonomy ............................. 40 2.2.3 Computing Applications .......................... 43 2.2.3.1 Scientific Parallel Applications ....................... 43 2.2.3.2 Enterprise Applications ........................... 44 2.2.4 Benchmarks ................................. 45 2.2.4.1 Resource Isolation .............................. 45 2.2.4.2 Parallel and Enterprise Benchmark Suites/Workloads .......... 46 2.2.5 Cloud Computing .............................. 48 2.2.5.1 Service Model ...............................
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