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Role of IoT, AI, and Big Data Analytics in Healthcare Industry
Published in Pushpa Singh, Divya Mishra, Kirti Seth, Transformation in Healthcare with Emerging Technologies, 2022
P. Sriramalakshmi, Srimathnath Thejasvi Vondivillu, A. Sri Krishna Govind
This system is considered to be the most complex of the cloud computing services. Similar to SaaS, PaaS delivers a platform in which software can be developed, created, tested, deployed, managed, and delivered via the internet. PaaS is widely used to create web or mobile apps quickly, without the need to set up the hardware components like servers, storage, and network required for development.60,61 PaaS can help cut time to code, add new development capabilities without the need to employ more skilled individuals, work with development teams across the globe, manage an application lifecycle efficiently, and develop multiple platforms more easily.70 Examples of this system include platforms like Heroku and Salesforce.60
SaaS and PaaS in Cloud
Published in Sunilkumar Manvi, Gopal K. Shyam, Cloud Computing, 2021
Sunilkumar Manvi, Gopal K. Shyam
PaaS is a category of Cloud computing services that provides a platform allowing customers to develop, run, and manage applications without the complexity of building and maintaining the infrastructure typically associated with developing and launching an application. As a layman, we can use the word PaaS and Middleware interchangeably as the use case for both of them is same i.e., Custom Application Development. Middleware is software that lies between an operating system and the applications running on it. Essentially functioning as hidden translation layer, middleware enables communication and data management for distributed applications (Figure 6.2). PaaS can be delivered in two ways: as a public Cloud service from a provider, where the consumer controls software deployment with minimal configuration options, and the provider provides the networks, servers, storage, OS, “middleware” (i.e.; java runtime,.net runtime, integration, etc.), database and other services to host the consumer's application; or as a private service (software or appliance) inside the firewall, or as software deployed on a public IaaS.
Mission-Critical Cloud Computing for Critical Infrastructures
Published in David Bakken, Krzysztof Iniewski, Smart Grids, 2017
Thoshitha Gamage, David Anderson, David Bakken, Kenneth Birman, Anjan Bose, Carl Hauser, Ketan Maheshwari, Robbert van Renesse
The PaaS model offers a development environment, middleware capabilities, and a deployment stack for application developers to build tailor-made applications or host prepurchased SaaS. Amazon Web Services (AWS), Google App Engine, and Microsoft Azure are a few examples of PaaS. In contrast to SaaS, PaaS does not abstract development life-cycle support, given that most end users in this model are application developers. Nevertheless, the abstraction aspect of cloud computing is still present in PaaS, where developers rely on underlying abstracted features such as infrastructure, operating system, backup and version control features, development and testing tools, runtime environment, workflow management, code security, and collaborative facilities.
Integrating optimal process and supplier selection in personalised product architecture design
Published in International Journal of Production Research, 2022
Changbai Tan, Kira Barton, S. Jack Hu, Theodor Freiheit
A limitation of the proposed method is that design decisions are made based on static data about customers, processes and suppliers. When markets and manufacturing environments are volatile, customer needs, process resources, and supply sources are subject to change. From the perspective of human recognition, customer understanding of products at an early design stage may be incomplete, but may become more clear as latent needs are gradually evoked as more tangible design details are added, i.e. from 3D digital model and physical prototypes. Meanwhile, new manufacturing processes and suppliers become available from time to time, which may lead to alternative decisions about product architecture design, and process and supplier selection. To capture the dynamics of market, process resources, and supply chain, the proposed decision model should be extended by incorporating an iterative product development optimisation strategy. One approach may be to integrate a Production-as-a-Service (PaaS) system (Balta et al. 2018) into this product architecture design framework. A PaaS system can provide the latest, most accurate process and supplier data (e.g. cost, lead time, and quality capability) on a service cloud, which facilitates the automation of iterative, concurrent decision optimisation on product architecture, manufacturing processes and suppliers.
Big Earth data: disruptive changes in Earth observation data management and analysis?
Published in International Journal of Digital Earth, 2020
Martin Sudmanns, Dirk Tiede, Stefan Lang, Helena Bergstedt, Georg Trost, Hannah Augustin, Andrea Baraldi, Thomas Blaschke
The backbone of big Earth data analytics is some type of distributed computing platform (e.g. clouds). Cloud computing services are broadly categorised into four types: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS) and Data as a Service (DaaS) (Yang et al. 2011). IaaS provides virtualised computing resources over the internet that can be used for storage, backup or big data analytics, with a pay-as-you-go structure. PaaS provides the hardware and software tools over the internet needed for applications development, testing and delivering. Microsoft Azure and Google App Engine are some of the most popular PaaS. SaaS is often referred to as ‘on-demand-software’, where cloud providers deliver software applications over the Internet, usually on a subscription basis. Common examples of SaaS include the ArcGIS Online (ESRI) cloud implementation, Microsoft Office or Google Gmail and apps. DaaS provides access to data discovery, access, and utilisation, including the software needed to interpret the data (Olson 2009; Yang et al. 2011).
The internet of things for smart manufacturing: A review
Published in IISE Transactions, 2019
Hui Yang, Soundar Kumara, Satish T.S. Bukkapatnam, Fugee Tsung
Cloud computing: Cloud computing provides internet-based computing services, including data storage, data management, KPI computation, data visualization and data analytics amongst others. There are three broad categories of cloud computing services, i.e., Infrastructure as a Service (IaaS) (Manvi and Krishna Shyam, 2014), Platform as a Service (PaaS) (Ferrer et al., 2016), and Software as a Service (SaaS) (Amiri, 2016). IaaS refers to cloud-based services of IT infrastructure such as operating systems, virtual machines, networks, and storage. PaaS provides an environment to develop, test, deploy, and manage IoT software applications. SaaS delivers the services of software applications over the cloud. Cloud computing allows IoT systems to gain ubiquitous access to shared computing and storage resources, thereby overcoming the disadvantage of limited computing resources and storage capability in the “Things.” In addition, the integration of cloud computing with IoT offers services such as machine learning and data analytics over the Internet, supporting intelligence and decision making in different contexts.