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Cloud Computing, Data Sources and Data Centers
Published in Diego Galar Pascual, Pasquale Daponte, Uday Kumar, Handbook of Industry 4.0 and SMART Systems, 2019
Diego Galar Pascual, Pasquale Daponte, Uday Kumar
Many PaaS providers supply the tools and services needed to build enterprise applications in the cloud. Google App Engine supports distributed web applications using Java, Python, PHP and Go.Red Hat OpenShift is a PaaS offering for creating open source applications using a wide variety of languages, databases and components.Heroku PaaS offers Unix-style container computing instances that run processes in isolated environments, while supporting languages such as Ruby, Python, Java, Scala, Cloture and Node.js.Microsoft Azure supports application development in .NET, Node.js, PHP, Python, Java and Ruby, and allows developers to use SDKs and visual studio to create and deploy applications.AWS Elastic Beanstalk allows users to create, deploy and scale web applications and services developed with Java, .NET, PHP, Node.js, Python, Ruby, Go and Docker on common servers, such as Apache, Nginx, Passenger and IIS.
Introduction
Published in John W. Rittinghouse, James F. Ransome, Cloud Computing, 2017
John W. Rittinghouse, James F. Ransome
An example of this model is the Google App Engine. According to Google, “Google App Engine makes it easy to build an application that runs reliably, even under heavy load and with large amounts of data.”7 The Google App Engine environment includes the following featuresDynamic web serving, with full support for common web technologiesPersistent storage with queries, sorting, and transactionsAutomatic scaling and load balancingAPIs for authenticating users and sending email using Google AccountsA fully featured local development environment that simulates Google App Engine on your computer
Cloud computing for big data
Published in Jun Deng, Lei Xing, Big Data in Radiation Oncology, 2019
Google App Engine is another platform for developing web applications using Google’s infrastructure using programming languages such as Java and Python and web frameworks such as Django, CherryPy, Pylons, and web2py. Specialized APIs, Google Accounts, URL Fetch, and email services are all supported by Google App Engine. Google App Engine also accommodates the need for managing the execution of applications by providing users with a web-based administration console. As of 2017, there was no cost associated with Google App Engine for storage usage of less than 500 MB and about 5 million page views per month.
PEFT-based Trade-off Schedule Plan for Execution IoT Applications in Cloud Environment
Published in IETE Journal of Research, 2021
Cloud computing is an emerging computing technique that uses the concept of virtualization of software and hardware to provide dynamically scalable services through internet depending on the user’s demand. In a few years, Service-Oriented Computing, Distributed Computing, and Parallel Computing have become the major attraction of researchers [1]. Cloud computing depends on the market-oriented business model in which the users pay-per-use for various computing, storage, and network services of Cloud. Three main delivery models of Clouds are: Software as a Service (SaaS), where the user uses the various developed applications like Google Apps, Salesforce.com, etc., but could not control the beneath environment [2]. Platform as a Service (PaaS) provides an application framework where users can develop and deploy their applications without buying and managing the underlying hardware and software like AWS and Google App Engine etc. [3] In the third type of delivery model, i.e. Infrastructure as a Service (IaaS), the user can choose the resources from a wide variety of different capabilities based on their requirements e.g. Amazon EC2, Globus, Nimbus, Eucalyptus, etc., [4].
A real-world service mashup platform based on data integration, information synthesis, and knowledge fusion
Published in Connection Science, 2021
Lei Yu, Yucong Duan, Kuan-Ching Li
We investigated not only commercial platform, but also academic cases. Researches on commercial and non-profit service orchestration platforms are discussed: OpenStack Heat (Couto et al., 2018), Windows Azure AppFabric / MarketPlace (including AppMarket), Amazon AWS Lambda, and Google App Engine. The combination of Windows Server and AppFabric (Kaufman & Garber, 2010) provides an easy-to-manage platform for developing, deploying, and reliably hosting middle-tier WCF/WF services. WCF stands for Windows Communication Foundation, an application development interface for data Communication developed by Microsoft. WCF is dedicated to service-oriented development. Windows Workflow Foundation (WF) is a general-purpose programming framework for creating interactive programmes that need to respond to signals from external entities. Malawski (Malawski et al., 2017) have developed prototype workflow executor functions using AWS Lambda, Villamizar et al. (2017) presents a cost comparison of a web application developed and deployed using the same scalable scenarios by AWS Lambda, and at the same time, (Abrahao & Insfran, 2017) proposed d a platform-independent monitoring middleware for cloud services. This middleware was implemented in both Microsoft Azure and Google App Engine to monitor cloud service quality. Using Google App Engine as a platform, (Nishida & Shinkawa, 2015) proposed s a modelling and simulation-based framework to predict the cloud performance. Basu et al. (2012) presents a performance case-study on implementing the building blocks of privacy-preserving collaborative filtering scheme in Java on the Google App Engine (GAE/J) cloud platform. Prodan et al. (2012) employs the Google App Engine (GAE) for high-performance parallel computing. Prodan and Sperk (2013) designed a generic master-slave framework that enables the implementation and integration of new algorithms by instantiating one interface and two abstract classes.
A Survey on Cloud Computing Applications in Smart Distribution Systems
Published in Electric Power Components and Systems, 2018
Jeovane V. de Sousa, Denis V. Coury, Ricardo A. S. Fernandes
Huang et al. [104] developed a cloud computing based platform for power system analysis, providing mainly three functions including load flow, contingency analysis, and data transformation services, using Google App Engine.