Innovations in Cloud Computing and Machine Learning Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 20 November 2025 | Viewed by 2009
Special Issue Editors
Interests: service computing; semantic web services; cloud computing; data mining; enterprise architecture
Interests: malware analysis; ransomware research; mobile device security; cybersecurity; security of home automation and cloud; privacy and security; consultancy; security of Internet of Things (IoT); secure computer networks; network security
Special Issue Information
Dear Colleagues,
Cloud computing and machine learning are two key technologies shaping the future of computing and data processing. Cloud computing provides scalable and flexible access to computational resources, enabling efficient data storage and processing, while machine learning allows systems to uncover patterns and derive insights from huge datasets. Together, these technologies are being applied across a variety of fields, creating solutions that address complex challenges and improve operational efficiency.
This Special Issue focuses on exploring advancements and applications at the intersection of cloud computing and machine learning. It aims to highlight research and practical developments that demonstrate innovative uses, address challenges, and improve the integration of these technologies.
Topics of interest include, but are not limited to, the following:
- Efficient deployment of machine learning models in cloud environments;
- Resource allocation and optimization for machine learning workloads;
- Data processing frameworks for large-scale machine learning in the cloud;
- Security, privacy, and compliance in cloud-based systems;
- Edge and cloud computing integration for distributed applications;
- Real-time data analytics using cloud computing infrastructures;
- Practical applications of cloud computing and machine learning in industries such as healthcare, finance, and logistics;
- Cost-effective strategies for scaling machine learning operations in the cloud;
- Case studies demonstrating the impact of cloud and machine learning technologies in real-world scenarios.
This Special Issue invites original research, reviews, and case studies that showcase the potential of combining cloud computing and machine learning. Contributions should emphasize practical approaches, technical challenges, and innovative solutions, providing valuable insights for researchers and practitioners alike.
Dr. Amal Alhosban
Dr. Abdullahi Arabo
Guest Editors
Manuscript Submission Information
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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. Mathematics 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 2600 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 computing
- machine learning
- scalability
- data processing
- resource optimization
- edge computing
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