scholarly journals PERFORMANCE ANALYSIS OF OPEN SOURCE STORAGE CLOUDS IN CLOUD COMPUTING

2012 ◽  
Vol 2 (2) ◽  
pp. 43-48
Author(s):  
Kumari Rani shaveta ◽  
Sangeeta Sharma
Keyword(s):  
Cloud Computing ◽  
Standard Deviation ◽  
Open Source ◽  
Performance Metrics ◽  
Memory Performance ◽  
Economic Value ◽  
Research Area ◽  
Memory Usage ◽  
Cpu Time ◽  
On Demand

Cloud computing is one of the latest research area that helps in storing the information permanently on the servers and manages the different resources for the requested users to provide on-demand services. In order to create the more usable and economic value based cloud computing, the principles, goals and structure of the cloud engineering is of vital importance. The objective of this study is to analyze the CPU and memory performance of different open source clouds. We will use different open source cloud to measure the different performance metrics like CPU time for downloading and uploading of file, memory usage while downloading and uploading the file, standard deviation of CPU usage and standard deviation of memory usage.

scholarly journals On-demand virtual research environments using microservices

2019 ◽  
Vol 5 ◽  
pp. e232 ◽  
Author(s):  
Marco Capuccini ◽  
Anders Larsson ◽  
Matteo Carone ◽  
Jon Ander Novella ◽  
Noureddin Sadawi ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Open Source ◽  
Scientific Community ◽  
Life Science ◽  
Scientific Applications ◽  
Infrastructure As A Service ◽  
On Demand ◽  
Research Environments ◽  
Cloud Providers

The computational demands for scientific applications are continuously increasing. The emergence of cloud computing has enabled on-demand resource allocation. However, relying solely on infrastructure as a service does not achieve the degree of flexibility required by the scientific community. Here we present a microservice-oriented methodology, where scientific applications run in a distributed orchestration platform as software containers, referred to as on-demand, virtual research environments. The methodology is vendor agnostic and we provide an open source implementation that supports the major cloud providers, offering scalable management of scientific pipelines. We demonstrate applicability and scalability of our methodology in life science applications, but the methodology is general and can be applied to other scientific domains.

Comparative Study on XEN, KVM, VSphere, and Hyper-V

2016 ◽  
pp. 233-261
Author(s):  
Prashanta Kumar Das
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Service Delivery ◽  
Comparative Study ◽  
Open Source ◽  
Qualitative Comparison ◽  
Hardware Virtualization ◽  
Delivery Model ◽  
On Demand ◽  
Computing Infrastructure

This Chapter provides a quantitative and qualitative comparison of four popular virtualization platforms, open-source hypervisors Xen, KVM and proprietary hypervisors VMware vSphere (ESXi), Microsoft Hyper-V. Cloud Computing is on Demand, Pay-per-use distributed computing service delivery model in which computing resources can be used as Utility like other utility such as water, electricity etc. as per requirement. Cloud computing has made it possible to provide virtually unlimited computing infrastructure i.e. IaaS on demand using virtualization technology. Intel and AMD have independently developed virtualization extensions to the x86 architecture referred to as hardware virtualization.

scholarly journals Performance Comparison between VM Based Webserver and Docker Container Webserver

2019 ◽  
Vol 8 (S2) ◽  
pp. 28-30
Author(s):  
A. Anand ◽  
A. Nisha Jebaseeli
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Performance Metrics ◽  
Performance Comparison ◽  
Light Weight ◽  
Performance Parameters ◽  
It Services ◽  
Network Bandwidth ◽  
On Demand ◽  
Processing Resources

Cloud computing is a type of Internet-based computing that provides shared computer processing resources, services and data to computers on demand. It offers an innovative business model for organizations to adopt IT services at a reduced cost with increased reliability and scalability. Virtualisation is one of backbone technology of cloud computing. But today, container based technology especially Docker offering better performance than Virtual Machine. It is famous for its light weight operation and better scaling. But still it is lagging in Disk I/O and network bandwidth intensive applications. So it is important to analyse and compare various performance parameters of VMs and Docker Images before implementation. Main Parameters will be CPU, Memory, Disk Utilization and Network Bandwidth. In this research paper, we compare performance metrics between Webserver deployed in Virtual machine and Docker webserver.

Performance Comparison of Web Backend And Database: A Case Study Of Node.JS, Golang and MySQL, MongoDB

2019 ◽  
Vol 13 ◽  
Author(s):  
Faried Effendy ◽  
Taufik ◽  
Bramantyo Adhilaksono
Keyword(s):  
Response Time ◽  
Open Source ◽  
Poisson Distribution ◽  
Mobile Application ◽  
Web Applications ◽  
Performance Comparison ◽  
Memory Usage ◽  
Data Traffic ◽  
Cpu Utilization

: Substantial research has been conducted to compare web servers or to compare databases, but very limited research combines the two. Node.js and Golang (Go) are popular platforms for both web and mobile application back-ends, whereas MySQL and Go are among the best open source databases with different characters. Using MySQL and MongoDB as databases, this study aims to compare the performance of Go and Node.js as web applications back-end regarding response time, CPU utilization, and memory usage. To simulate the actual web server workload, the flow of data traffic on the server follows the Poisson distribution. The result shows that the combination of Go and MySQL is superior in CPU utilization and memory usage, while the Node.js and MySQL combination is superior in response time.

scholarly journals OpenStack: Toward an Open-source Solution for Cloud Computing

2012 ◽  
Vol 55 (3) ◽  
pp. 38-42 ◽  
Author(s):  
Omar Sefraoui ◽  
Mohammed Aissaoui ◽  
Mohsine Eleuldj
Keyword(s):  
Cloud Computing ◽  
Open Source

On-Demand Public Transit: A Markovian Continuous Approximation Model

2021 ◽  
Author(s):  
Daniel F. Silva ◽  
Alexander Vinel ◽  
Bekircan Kirkici
Keyword(s):  
System Performance ◽  
Performance Metrics ◽  
Public Transit ◽  
Continuous Approximation ◽  
Efficient Operation ◽  
Fleet Sizing ◽  
On Demand ◽  
Single Vehicle ◽  
Transit Agencies ◽  
Using Data

With recent advances in mobile technology, public transit agencies around the world have started actively experimenting with new transportation modes, many of which can be characterized as on-demand public transit. Design and efficient operation of such systems can be particularly challenging, because they often need to carefully balance demand volume with resource availability. We propose a family of models for on-demand public transit that combine a continuous approximation methodology with a Markov process. Our goal is to develop a tractable method to evaluate and predict system performance, specifically focusing on obtaining the probability distribution of performance metrics. This information can then be used in capital planning, such as fleet sizing, contracting, and driver scheduling, among other things. We present the analytical solution for a stylized single-vehicle model of first-mile operation. Then, we describe several extensions to the base model, including two approaches for the multivehicle case. We use computational experiments to illustrate the effects of the inputs on the performance metrics and to compare different modes of transit. Finally, we include a case study, using data collected from a real-world pilot on-demand public transit project in a major U.S. metropolitan area, to showcase how the proposed model can be used to predict system performance and support decision making.

scholarly journals Influence of Cloud Based Mobile Learning Applications on User Experiences: A Review Study in the Context of Jordan

2017 ◽  
Vol 11 (4) ◽  
pp. 202 ◽  
Author(s):  
Osama Harfoushi
Keyword(s):  
Cloud Computing ◽  
Mobile Learning ◽  
Mobile Applications ◽  
Educational Institution ◽  
Research Area ◽  
Traditional Learning ◽  
Learning Methods ◽  
User Experiences ◽  
Main Research ◽  
Innovative Tool

Beside the increasing trend of cloud computing and mobile applications, the use of cloud based mobile learning applications is also mounting. Almost every e-commerce service provider offers cloud based mobile learning applications so that they can target more visitors and ultimately increase their sales. The usability of cloud based mobile applications is not only grounded in e-commerce platforms but it also ease out mobile learning processes. Most of the educational institutes are now offering cloud based mobile applications so their students can navigate to their knowledge portal more easily and download relevant material or submit assignments respectively. The main research area of this article is to explore how cloud based mobile learning applications can be utilized more effectively and what impact they imply on its users. Also, this research compares the mobile learning methods versus traditional learning methods. The study is evidence from Jordan and the major part of the research will be carried out through surveying literature, reports, content, and national and international databases in order to critically discuss the interactions between clouds based mobile learning application and user experiences. Published researches, published reports, books and articles has been included in the review.  Review of literature shows that mobile cloud computing is rising in Jordan and have significant impact on mobile learning of Jordanian students. Further, M-learning indeed an innovative tool for learning and it helps the users in many ways. In traditional learning, students used to spend their money on books and other written content. Findings of this study are helpful for the educational institution so they will come to know about user experiences of utilizing these cloud based mobile applications.

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