scholarly journals The Cloud's Cloudy Moment: A Systematic Survey of Public Cloud Service Outage

2013 ◽  
Vol 2 (5) ◽  
Author(s):  
Zheng Li ◽  
Mingfei Liang ◽  
Liam O'Brien ◽  
He Zhang
Keyword(s):  
Cloud Service ◽  
Public Cloud ◽  
Systematic Survey

System Benchmarking on Public Clouds

2015 ◽  
pp. 37-50
Author(s):  
Sanjay P. Ahuja ◽  
Thomas F. Furman ◽  
Kerwin E. Roslie ◽  
Jared T. Wheeler
Keyword(s):  
Service Providers ◽  
Cluster Formation ◽  
Cloud Service ◽  
Vital Role ◽  
Cloud Services ◽  
System Level ◽  
Public Cloud ◽  
Cloud Providers ◽  
Set Up ◽  
Levels Of Service

There are several public cloud providers that provide service across different cloud models such as IaaS, PaaS, and SaaS. End users require an objective means to assess the performance of the services being offered by the various cloud providers. Benchmarks have typically been used to evaluate the performance of various systems and can play a vital role in assessing performance of the different public cloud platforms in a vendor neutral manner. Amazon's EC2 Service is one of the leading public cloud service providers and offers many different levels of service. The research in this chapter focuses on system level benchmarks and looks into evaluating the memory, CPU, and I/O performance of two different tiers of hardware offered through Amazon's EC2. Using three distinct types of system benchmarks, the performance of the micro spot instance and the M1 small instance are measured and compared. In order to examine the performance and scalability of the hardware, the virtual machines are set up in a cluster formation ranging from two to eight nodes. The results show that the scalability of the cloud is achieved by increasing resources when applicable. This chapter also looks at the economic model and other cloud services offered by Amazon's EC2, Microsoft's Azure, and Google's App Engine.

On the Use of System-Level Benchmarks for Comparing Public Cloud Environments

2019 ◽  
pp. 24-38
Author(s):  
Sanjay P. Ahuja
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Cluster Formation ◽  
Cloud Service ◽  
System Level ◽  
Public Cloud ◽  
Related Information ◽  
Computing Environments ◽  
Set Up ◽  
Levels Of Service

The proliferation of public cloud providers and services offered necessitate that end users have benchmarking-related information that help compare the properties of the cloud computing environment being provided. System-level benchmarks are used to measure the performance of overall system or subsystem. This chapter surveys the system-level benchmarks that are used for traditional computing environments that can also be used to compare cloud computing environments. Amazon's EC2 Service is one of the leading public cloud service providers and offers many different levels of service. The research in this chapter focuses on system-level benchmarks and looks into evaluating the memory, CPU, and I/O performance of two different tiers of hardware offered through Amazon's EC2. Using three distinct types of system benchmarks, the performance of the micro spot instance and the M1 small instance are measured and compared. In order to examine the performance and scalability of the hardware, the virtual machines are set up in a cluster formation ranging from two to eight nodes.

Performance Evaluation of Public IaaS Clouds for Web 2.0 Applications Using CloudStone Benchmark

2018 ◽  
pp. 292-314
Author(s):  
Sanjay P. Ahuja ◽  
Neha Soni
Keyword(s):  
Web 2.0 ◽  
Web Application ◽  
Cloud Service ◽  
Cloud Services ◽  
Public Cloud ◽  
Data Intensive ◽  
Social Events ◽  
Amazon Ec2 ◽  
And Performance ◽  
Workload Generator

Web 2.0 applications have become ubiquitous over the past few years because they provide useful features such as a rich, responsive graphical user interface that supports interactive and dynamic content. Social networking websites, blogs, auctions, online banking, online shopping and video sharing websites are noteworthy examples of Web 2.0 applications. The market for public cloud service providers is growing rapidly, and cloud providers offer an ever-growing list of services. As a result, developers and researchers find it challenging when deciding which public cloud service to use for deploying, experimenting or testing Web 2.0 applications. This study compares the scalability and performance of a social-events calendar application on two Infrastructure as a Service (IaaS) cloud services – Amazon EC2 and HP Cloud. This study captures and compares metrics on three different instance configurations for each cloud service such as the number of concurrent users (load), as well as response time and throughput (performance). Additionally, the total price of the three different instance configurations for each cloud service is calculated and compared. This comparison of the scalability, performance and price metrics provides developers and researchers with an insight into the scalability and performance characteristics of the three instance configurations for each cloud service, which simplifies the process of determining which cloud service and instance configuration to use for deploying their Web 2.0 applications. This study uses CloudStone – an open-source, three-tier web application benchmarking tool that simulates Web 2.0 application activities – as a realistic workload generator and to capture the intended metrics. The comparison of the collected metrics indicates that all of the tested Amazon EC2 instance configurations provide better scalability and lower latency at a lower cost than the respective HP Cloud instance configurations; however, the tested HP Cloud instance configurations provide a greater storage capacity than the Amazon EC2 instance configurations, which is an important consideration for data-intensive Web 2.0 applications.

A Model-Based Deployment Framework of Integrated Public Cloud Service

2012 ◽  
Author(s):  
Ze-Yuan Wang ◽  
Qing Li ◽  
Zhi-Chao Cao ◽  
Wei-Hua Li ◽  
Jun Li ◽  
...  
Keyword(s):  
Cloud Service ◽  
Public Cloud ◽  
Model Based

Challenges and Opportunities in High Performance Cloud Computing

2019 ◽  
pp. 85-114 ◽  
Author(s):  
Manoj Himmatrao Devare
Keyword(s):  
High Performance ◽  
Cloud Service ◽  
Cloud Environment ◽  
Public Cloud ◽  
Distributed Environment ◽  
Processor Architectures ◽  
Challenges And Opportunities ◽  
Performance Computing ◽  
Energy Engineering ◽  
Hpc Cloud

The scientist, engineers, and researchers highly need the high-performance computing (HPC) services for executing the energy, engineering, environmental sciences, weather, and life science simulations. The virtual machine (VM) or docker-enabled HPC Cloud service provides the advantages of consolidation and support for multiple users in public cloud environment. Adding the hypervisor on the top of bare metal hardware brings few challenges like the overhead of computation due to virtualization, especially in HPC environment. This chapter discusses the challenges, solutions, and opportunities due to input-output, VMM overheads, interconnection overheads, VM migration problems, and scalability problems in HPC Cloud. This chapter portrays HPC Cloud as highly complex distributed environment consisting of the heterogeneous types of architectures consisting of the different processor architectures, inter-connectivity techniques, the problems of the shared memory, distributed memory, and hybrid architectures in distributed computing like resilience, scalability, check-pointing, and fault tolerance.

Challenges and Opportunities in High Performance Cloud Computing

2021 ◽  
pp. 1989-2018
Author(s):  
Manoj Himmatrao Devare
Keyword(s):  
High Performance ◽  
Cloud Service ◽  
Cloud Environment ◽  
Public Cloud ◽  
Distributed Environment ◽  
Processor Architectures ◽  
Challenges And Opportunities ◽  
Performance Computing ◽  
Energy Engineering ◽  
Hpc Cloud

The scientist, engineers, and researchers highly need the high-performance computing (HPC) services for executing the energy, engineering, environmental sciences, weather, and life science simulations. The virtual machine (VM) or docker-enabled HPC Cloud service provides the advantages of consolidation and support for multiple users in public cloud environment. Adding the hypervisor on the top of bare metal hardware brings few challenges like the overhead of computation due to virtualization, especially in HPC environment. This chapter discusses the challenges, solutions, and opportunities due to input-output, VMM overheads, interconnection overheads, VM migration problems, and scalability problems in HPC Cloud. This chapter portrays HPC Cloud as highly complex distributed environment consisting of the heterogeneous types of architectures consisting of the different processor architectures, inter-connectivity techniques, the problems of the shared memory, distributed memory, and hybrid architectures in distributed computing like resilience, scalability, check-pointing, and fault tolerance.

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