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Applied Sciences
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Advanced Technologies and Applications of Cloud Platforms
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Advanced Technologies and Applications of Cloud Platforms

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (30 May 2023) | Viewed by 13313

Special Issue Editors

Prof. Dr. Joon-Min Gil

E-Mail Website
Guest Editor
Department of Computer Science, Catholic University of Daegu, Gyeongsan 38430, Korea
Interests: artificial intelligence; machine learning; big data computing; cloud computing; edge/fog computing; distributed and parallel computing
Special Issues, Collections and Topics in MDPI journals
Dr. Jisu Park

E-Mail Website
Guest Editor
Department of Computer Science Engineering, Jeonju University, Jeonju, 55069, Republic of Korea
Interests: AI; big data analysis; cloud
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cloud computing offers on-demand access to computing power along with modern data and application services for developers. Ccloud-native computing is an approach to building and running applications that exploits the advantages of the cloud computing delivery model by incorporating DevOps, continuous delivery, microservices, and containers.

To fully benefit from cloud-native applications, cloud platforms should be cost-effective, scalabile, portabile, reliabile, and easy to maintain, traits that are hard to implement efficiently due to their inherent complex nature. Motivated by the above factors, we invite the submission of papers to the present Special Issue, “Advanced Technologies and Applications of Cloud Platforms. Original research, reviews, case studys, and report articles are all welcome.

Topics of interest include, but are not limited to:

  • Testbed and extensive simulations of microservices and cloud-native solutions.
  • Optimization for containers, microservices, and cloud-native solutions.
  • Fog and edge infrastructures integration for containers, microservices, and cloud-native solutions.
  • Formal proof, methods, models, and techniques for containers, microservices and cloud-native solutions.
  • Deployment and deploy automation in containers, microservices, and cloud-native solutions.
  • Adaptation, exploitation, and deployment for containers, microservices and cloud-native solutions.
  • Model-driven design and development of containers, microservices, and cloud-native solutions.
  • Considerations of availability, fault-resilience, and scalability in containers, microservices, and cloud-native solutions.
  • Serverless applications and function-as-a-service solutions.
  • Fault isolations in containers, microservices, and cloud-native solutions.
  • Correctness and verification methods of microservices and cloud-native solutions. 
  • Best practices and empirical studies on containers, microservices, and cloud-native solutions.
  • Infrastructure and integration components for containers, microservices, and cloud-native solutions.
  • Design principles and architectural refactoring of containers, microservices, and cloud-native solutions.

Prof. Dr. Joon-Min Gil
Dr. Jisu Park
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cloud platforms
  • cloud architecture
  • cloud infrastructure
  • containers
  • microservices
  • Cloud-native solutions
  • serverless computing
  • serverless architecture serverless applications
  • fault isolations
  • edge/fog computing
  • edge/fog architecture
  • edge/fog application

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

22 pages, 7214 KiB  
Article
A Comparative Assessment of JVM Frameworks to Develop Microservices
by Łukasz Wyciślik, Łukasz Latusik and Anna Małgorzata Kamińska
Appl. Sci. 2023, 13(3), 1343; https://doi.org/10.3390/app13031343 - 19 Jan 2023
Cited by 3 | Viewed by 4427
Abstract
With the ever-increasing wide spread of the Internet, the number of web services, web applications, and IoT devices is growing every year. This brings a number of challenges, both in terms of network bandwidth and the ability to scale individual computing nodes, whether [...] Read more.
With the ever-increasing wide spread of the Internet, the number of web services, web applications, and IoT devices is growing every year. This brings a number of challenges, both in terms of network bandwidth and the ability to scale individual computing nodes, whether they are large systems running in computing clouds or smaller IoT devices running closer to their data sources (so-called edge computing). In both cases, the way to cope with handling large numbers of users/requests is horizontal scaling, the implementation of which today is using the concept of microservices. However, the concept itself is not enough—we need ready-made application frameworks that allow us to easily implement and deploy efficient services. In the case of the Java ecosystem, which is one of the most mature platforms for enterprise-class software development, several frameworks dedicated to the development of microservices have been engineered recently. These tools support system developers in implementing communication, computation, and data storage mechanisms. However, so far, there is a lack of comparative analysis of individual solutions in the scholarly discourse to assess their performance and production maturity, so the authors in this article try to fill this gap. Based on synthetic tests developed by the authors, the most promising frameworks (Spring Boot, Micronaut, Quarkus) were analyzed both in terms of computational, compilation, or deployment performance. The results obtained can help system architects make rational and evidence-driven choices of system architecture and technology stacks. Full article
(This article belongs to the Special Issue Advanced Technologies and Applications of Cloud Platforms)
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16 pages, 1419 KiB  
Article
Design and Implementation of Cloud Docker Application Architecture Based on Machine Learning in Container Management for Smart Manufacturing
by Byoung Soo Kim, Sang Hyeop Lee, Ye Rim Lee, Yong Hyun Park and Jongpil Jeong
Appl. Sci. 2022, 12(13), 6737; https://doi.org/10.3390/app12136737 - 3 Jul 2022
Cited by 9 | Viewed by 8009
Abstract
Manufacturers are expanding their business-process innovation and customized manufacturing to reduce their information technology costs and increase their operational efficiency. Large companies are building enterprise-wide hybrid cloud platforms to further accelerate their digital transformation. Many companies are also introducing container virtualization technology to [...] Read more.
Manufacturers are expanding their business-process innovation and customized manufacturing to reduce their information technology costs and increase their operational efficiency. Large companies are building enterprise-wide hybrid cloud platforms to further accelerate their digital transformation. Many companies are also introducing container virtualization technology to maximize their cloud transition and cloud benefits. However, small- and mid-sized manufacturers are struggling with their digital transformation owing to technological barriers. Herein, for small- and medium-sized manufacturing enterprises transitioning onto the cloud, we introduce a Docker Container application architecture, a customized container-based defect inspection machine-learning model for the AWS cloud environment developed for use in small manufacturing plants. By linking with open-source software, the development was improved and a datadog-based container monitoring system, built to enable real-time anomaly detection, was implemented. Full article
(This article belongs to the Special Issue Advanced Technologies and Applications of Cloud Platforms)
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