Performance Evaluation of Popular Cloud IaaS Providers (original) (raw)
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IEEE Transactions on Services Computing, 2014
The increasing popularity of clouds drives researchers to find answers to a large variety of new and challenging questions. Through extensive experimental measurements, we show variance in performance and scalability of clouds for two non-trivial scenarios. In the first scenario, we target the public Infrastructure as a Service (IaaS) clouds, and study the case when a multi-tier application is migrated from a traditional datacenter to one of the three IaaS clouds. To validate our findings in the first scenario, we conduct similar study with three private clouds built using three mainstream hypervisors. We used the RUBBoS benchmark application and compared its performance and scalability when hosted in Amazon EC2, Open Cirrus, and Emulab. Our results show that a best-performing configuration in one cloud can become the worst-performing configuration in another cloud. Subsequently, we identified several system level bottlenecks such as high context switching and network driver processing overheads that degraded the performance. We experimentally evaluate concrete alternative approaches as practical solutions to address these problems. We then built the three private clouds using a commercial hypervisor (CVM), Xen, and KVM respectively and evaluated performance characteristics using both RUBBoS and Cloudstone benchmark applications. The three clouds show significant performance variations; for instance, Xen outperforms CVM by 75% on the read-write RUBBoS workload and CVM outperforms Xen by over 10% on the Cloudstone workload. These observed problems were confirmed at a finer granularity through micro-benchmark experiments that measure component performance directly.
Performance Analysis for Large IaaS Clouds
2014
IaaS clouds are major enablers of data-intensive cloud applications because they provide necessary computing capacity for managing Big Data environments. In a typical IaaS cloud, virtual machine (VM) instances deployed on physical machines (PM) are provided to the users for their computing needs. Recently, IaaS cloud providers are realizing that merely providing the basic functionalities for Big Data processing is not sufficient to survive intense business competitions. Rather, the performance of the cloud provided service is an equally important factor when a CONTENTS
Performance Analysis of Public Cloud Computing Providers
2016
The objective of this paper is to perform a comprehensive performance comparison of public cloud services for computing and to analyze the correlation between their prices and performance. Eight representative public cloud providers were divided into two groups using market share: small cloud providers and large cloud providers. Results revealed that these offered computing services vary widely in performance and price; most small cloud providers have more stable and better computing performance than large cloud providers; the performance of CPU impact price significantly.
Performance Issues with Cloud Computing
International Journal of Engineering Applied Sciences and Technology, 2021
Cloud computing is key for today's fast world. It serves across all the domains. Be it business, educational, public, or private sector, etc. Its application can be observed anywhere. Its overall concept and its analysis of services and model are presented here. Mainly cloud has 3 delivery models. Saas (Software as a service), Paas(Platform as a service), and Iaas (Infrastructure as a service). We explored these with their performances and interdependencies. Cloud adoption has its performance limitation and solutions to overcome these challenges are provided here. Also, cloud delivery models are discussed. Performance factors are very important for as a whole cloud computing success, where it adds its ideal cost of services, its reliability, and its scalability constitutes as its pillar factors.
IaaS Cloud Benchmarking: Approaches, Challenges, and Experience
In 5th Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS 2012), held in conjunction with SC, Salt Lake City, Utah, USA, Nov 2012., 2012
Infrastructure-as-a-Service (IaaS) cloud computing is an emerging commercial infrastructure paradigm under which clients (users) can lease resources when and for how long needed, under a cost model that reflects the actual usage of resources by the client. For IaaS clouds to become mainstream technology and for current cost models to become more client-friendly, benchmarking and comparing the non-functional system properties of various IaaS clouds is important, especially for the cloud users. In this article we focus on the IaaS cloud-specific elements of benchmarking, from a user's perspective. We propose a generic approach for IaaS cloud benchmarking, discuss numerous challenges in developing this approach, and summarize our experience towards benchmarking IaaS clouds. We argue for an experimental approach that requires, among others, new techniques for experiment compression, new benchmarking methods that go beyond blackbox and isolated-user testing, new benchmark designs that are domain-specific, and new metrics for elasticity and variability.
Comparison Among Cloud Technologies and Cloud Performance
jastt, 2020
The cloud is the best method used for the utilization and organization of data. The cloud provides many resources for us via the internet. There are many technologies used in cloud computing systems; each one uses a different kind of protocols and methods. Many tasks can execute on different servers per second, which cannot execute on their computer. The most popular technologies used in the cloud system are Hadoop, Dryad, and another map reducing framework. Also, there are many tools used to optimize the performance of the cloud system, such as Cap3, HEP, and Cloudburst. This paper reviews in detail the cloud computing system, its used technologies, and the best technologies used with it according to multiple factors and criteria such as the procedure cost, speed cons and pros. Moreover, A comprehensive comparison of the tools used for the utilization of cloud computing systems is presented.
Performance Analysis of Cloud Computing | IJSRDV6I90125
IJSRD - International Journal for Scientific Research and Development, 2018
— Cloud computing is a method or technique for enabling convenient, on demand network access to a shared pool of computing resources (such as computer networks, servers, applications, storage, and services) that can be continuously provisioned and released with minimum management efforts. In this paper we have used some of the existing performance monitoring tools and techniques popular among variety of users. During this study a number of factors such as response time, bandwidth and latency etc. have been determined. Considering the frequency of factors appearing from the review work it has been inferred that the cloud response time is very crucial for the cloud performance and selected for further study.
Performance Evaluation for Virtual Server Management in Cloud Computing
2013
Cloud Computing is defined as a type of parallel and distributed system consisting of a collection of interconnected and virtualized computers. It is based on service-level agreements that established between service providers and consumers. Cloud Computing opens up many new possibilities for Internet application developers. The VMware is used to integrate the virtual servers which are used for performance analysis.
IJERT-Comparative Performance Analysis of the Virtualization Technologies in Cloud Computing
International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/comparative-performance-analysis-of-the-virtualization-technologies-in-cloud-computing https://www.ijert.org/research/comparative-performance-analysis-of-the-virtualization-technologies-in-cloud-computing-IJERTV3IS090667.pdf A hypervisor or virtual machine monitor (VMM) is a piece of computer software, firmware or hardware that creates and runs virtual machines which makes multi-tenancy possible. Multi-tenancy allows multiple tenants to coexist in the same physical machine sharing its resources and at the same time, creates an isolated environment for each of them. Cloud service providers (CSP) can maximize their infrastructures using this architecture by allocating resources from physical machines that are not being fully used. Multi tenancy can be obtained by virtualization, which is the future in the IT world. This research paper provides concept of virtualization along with the performance comparison of some common virtualization technologies using many benchmarks which is chosen as it gives a good idea how the hypervisor's performance is. First method of comparison chosen is features comparison, further those virtualization techniques are technically compared along with File I/O benchmark, CPU benchmark sequential read-write performance and memory and cache performance of the VMs running at the top of the virtualized layer is studied, ultimately concludes giving an overall guideline to choose a wise hypervisor depending upon the purpose.
PERFORMANCE ANALYSIS OF PaaS CLOUD COMPUTING SYSTEM
2016
Abstract: Cloud computing is business infrastructure paradigm that promising to remove the need for organizations to keep up an exclusive computing hardware. Cloud computing provides to users with various capabilities to store and process the data in third-party data centers. Cloud computing maximizes the effectiveness of shared resources. During the use of time sharing and virtualization cloud address with the particular set of material resources in a large scaled user‟s base with different needs. In this paper computing the performance of Platform-as-a-Service (PaaS) model and integrating the mechanisms to capture the virtual machine migrations. We study the cloud services on different large applications. In this paper we are presenting the performance of Platform-as-a-Service (PaaS) by using systematic model to perform end-to-end analysis of a cloud service. The systematic model designed by using scheduling algorithm i.e., Adaptive First Come First Serve under different job sizes...