Creating a Custom Virtual Private Cloud and Launch an Elastic Compute Cloud (EC2) Instance in Your Virtual Private Cloud

2020 ◽  
Vol 17 (9) ◽  
pp. 4509-4514
Author(s):  
M. Niranjanamurthy ◽  
M. P. Amulya ◽  
N. M. Niveditha ◽  
P. Dayananda
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Hard Disk ◽  
Private Cloud ◽  
Processing Stage ◽  
Remote Server ◽  
Amazon Web Services ◽  
Amazon Ec2 ◽  
The Web

Cloud Computing is regarded to as putting away and getting to data over the web. The hard disk of your PC doesn’t hold this data. In Cloud computing, you can get to information from a remote server. Amazon Web Services (AWS) enables adaptable, solid, versatile, simple to-utilize and practical Cloud computing arrangements. AWS is an extensive, simple to utilize processing stage offered Amazon. A virtual private cloud (VPC) is devoted to the AWS account which is in the AWS cloud that acts coherently detached with different virtual systems. Amazon EC2 is a secure web administration which allows register with the modifiable limit in the cloud .In this work, we are giving route subtleties of Creating a custom VPC and dispatch an EC2 Instance in your VPC.

scholarly journals Biomedical Cloud Computing With Amazon Web Services

2011 ◽  
Vol 7 (8) ◽  
pp. e1002147 ◽  
Author(s):  
Vincent A. Fusaro ◽  
Prasad Patil ◽  
Erik Gafni ◽  
Dennis P. Wall ◽  
Peter J. Tonellato
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Amazon Web Services

scholarly journals An Investigation of Microsoft Azure and Amazon Web Services from Users’ Perspectives

2019 ◽  
Vol 14 (10) ◽  
pp. 217 ◽  
Author(s):  
Rizik M. H. Al-Sayyed ◽  
Wadi’ A. Hijawi ◽  
Anwar M. Bashiti ◽  
Ibrahim AlJarah ◽  
Nadim Obeid ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Service Level Agreement ◽  
Service Level ◽  
Point Of View ◽  
Survey Study ◽  
Utility Computing ◽  
User Survey ◽  
Amazon Web Services ◽  
Microsoft Azure

Cloud computing is one of the paradigms that have undertaken to deliver the utility computing concept. It views computing as a utility similar to water and electricity. We aim in this paper to make an investigation of two highly efficacious Cloud platforms: Microsoft Azure (Azure) and Amazon Web Services (AWS) from users’ perspectives the point of view of users. We highlight and compare in depth the features of Azure and AWS from users’ perspectives. The features which we shall focus on include (1) Pricing, (2) Availability, (3) Confidentiality, (4) Secrecy, (5) Tier Account and (6) Service Level Agreement (SLA). The study shows that Azure is more appropriate when considering Pricing and Availability (Error Rate) while AWS is more appropriate when considering Tier account. Our user survey study and its statistical analysis agreed with the arguments made for each of the six comparisons factors.

scholarly journals IOT based e – health care system

2018 ◽  
Vol 7 (2.25) ◽  
pp. 43 ◽  
Author(s):  
R Chandrasekaran ◽  
Syed Uzma Farheen ◽  
R J.Hemalatha ◽  
Bincy Babu ◽  
Josephin Arockiya Dhivya ◽  
...  
Keyword(s):  
Health Care ◽  
Cloud Computing ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Physiological Parameters ◽  
Private Cloud ◽  
Computing Power ◽  
The Subject ◽  
Sensor Monitoring ◽  
The Web

One of the most important technological evolutions of our time is CLOUD COMPUTING, which describes the web computing power to store and process the information. The evolution and advancements are swiftly increasing in remote monitoring and Telemedicine. This paper aims at transmitting the physiological parameters of the subject to the private cloud called Thing Speak, an IOT based Sensor monitoring system. The physiological parameters are sent to the cloud via ESP8266 (IOT device). The cloud computing helps the physician to be connected with the patient’s data and it is helpful in monitoring the patients at any time through internet.  

CONDE: Climate simulation ON DEmand using HPCaaS

2020 ◽  
Author(s):  
Diego A. Pérez Montes ◽  
Juan A. Añel ◽  
Javier Rodeiro
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Climate Simulation ◽  
On Demand ◽  
Ensemble Simulations ◽  
Amazon Web Services ◽  
Computing Environments ◽  
Microsoft Azure

<p><strong>CONDE (Climate simulation ON DEmand)</strong> is the final result of our work and research about climate and meteorological simulations over an HPC as a Service (HPCaaS) model. On our architecture we run very large climate ensemble simulations using a, adapted, WRF version that is executed on-demand and that can be deployed over different Cloud Computing environments (like Amazon Web Services, Microsoft Azure or Google Cloud) and that uses BOINC as middleware for the tasks execution and results gathering. Here, we also present as well some basic examples of applications and experiments to verify that the simulations ran in our system are correct and show valid results. </p>

Serverless Computing Using Amazon Web Services

2020 ◽  
Vol 17 (8) ◽  
pp. 3581-3585
Author(s):  
M. S. Roobini ◽  
Selvasurya Sampathkumar ◽  
Shaik Khadar Basha ◽  
Anitha Ponraj
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Software Design ◽  
Web Application ◽  
Cloud Provider ◽  
Business Logic ◽  
Compute Model ◽  
Amazon Web Services ◽  
The Way

In the last decade cloud computing transformed the way in which we build applications. The boom in cloud computing helped to develop new software design and architecture. Helping the developers to focus more on the business logic than the infrastructure. FaaS (function as a service) compute model it gave developers to concentrate only on the application code and rest of the factors will be taken care by the cloud provider. Here we present a serverless architecture of a web application built using AWS services and provide detail analysis of lambda function and micro service software design implemented using these AWS services.

scholarly journals Long Paddock: climate risk and grazing information for Australian rangelands and grazing communities

2019 ◽  
Vol 41 (3) ◽  
pp. 225 ◽  
Author(s):  
G. Stone ◽  
R. Dalla Pozza ◽  
J. Carter ◽  
G. McKeon
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Natural Resource ◽  
Climate Risk ◽  
Resource Base ◽  
Computing Platform ◽  
Amazon Web Services ◽  
Cloud Computing Platform ◽  
Natural Resource Base ◽  
Tailored Information

The Queensland Government’s Long Paddock website has been redeveloped on Amazon Web Services cloud computing platform, to provide Australian rangelands and grazing communities (i.e. rural landholders, managers, pastoralists (graziers), researchers, advisors, students, consultants and extension providers) with easier access to seasonal climate and pasture condition information. The website provides free, tailored information and services to support management decisions to maximise productivity, while maintaining the natural resource base. For example, historical rainfall and pasture analyses (i.e. maps, posters and data) have been developed to assist in communicating the risk of multi-year droughts that are a feature of Queensland’s highly variable climate.

scholarly journals Successes and struggles with computational reproducibility: Lessons from the Fragile Families Challenge

2019 ◽  
Author(s):  
David Liu ◽  
Matthew Salganik
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Fragile Families ◽  
Special Issue ◽  
Computing Environment ◽  
Raw Data ◽  
Academic Researchers ◽  
Amazon Web Services ◽  
Software Engineers ◽  
Published Paper

Reproducibility is fundamental to science, and an important component of reproducibility is computational reproducibility: the ability of a researcher to recreate the results in a published paper using the original author's raw data and code. Although most people agree that computational reproducibility is important, it is still difficult to achieve in practice. In this paper, we describe our approach to enabling computational reproducibility for the 12 papers in this special issue of Socius about the Fragile Families Challenge. Our approach draws on two tools commonly used by professional software engineers but not widely used by academic researchers: software containers (e.g., Docker) and cloud computing (e.g., Amazon Web Services). These tools enabled us to standardize the computing environment around each submission, which will ease computational reproducibility both today and in the future. Drawing on our successes and struggles, we conclude with recommendations to authors and journals.

Assessing Experimental Private Cloud Using Web of System Performance Model

2017 ◽  
Vol 9 (2) ◽  
pp. 21-35 ◽  
Author(s):  
Adib Habbal ◽  
Siti Aminah Abdullah ◽  
Emmanuel O.C. Mkpojiogu ◽  
Suhaidi Hassan ◽  
Nabil Benamar
Keyword(s):  
Cloud Computing ◽  
System Performance ◽  
Teaching And Learning ◽  
Virtual Machines ◽  
Performance Model ◽  
Private Cloud ◽  
University Environment ◽  
Virtual Lab ◽  
Sample Testing ◽  
The Web

Cloud computing has attracted the attention of educational and research institutions as a way to support modern trends in teaching and learning. This article describes the performance assessment of a private cloud within a university environment using the Web of System Performance (WOSP) model. A survey was carried out to measure the respondents' attitude towards the use of private cloud in which students and experts serve as sample. Testing was conducted by designing a virtual lab consisting of a number of virtual machines operated by a selected sample. The results showed that the usage of cloud computing in university has good perceived system performance judging from how it fares in the constituent parts of the WOSP model. Furthermore, the study revealed that usability and flexibility outperformed criterion like security. Moreover, several non-functional criteria outperformed functionality. In short, the knowledge and results presented from assessing a private cloud using WOSP model could be beneficial for users, designers and managers of private clouds especially in universities.

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