Research on Cloud Computing and Big Data

Dear Colleagues,

In recent years, cloud computing and big data have emerged as transformative technologies that are reshaping industries and redefining the landscape of digital innovation. The seamless integration of these technologies allows for the efficient management and analysis of vast amounts of data, enabling organizations to derive actionable insights and drive informed decision making. Cloud computing, with its scalable and flexible infrastructure, has become a critical enabler of big data analytics, providing the computational power and storage capacity required to handle the growing volume, variety, and velocity of data.

The convergence of cloud computing and big data has paved the way for the development of intelligent systems that can adapt to dynamic environments and deliver personalized services at scale. As organizations increasingly rely on cloud-based solutions to manage their data, there is a pressing need for research that addresses the challenges of data security, privacy, and compliance, as well as the optimization of cloud resources for big data processing.

This Special Issue on "Research on Cloud Computing and Big Data" seeks to explore the latest advancements, challenges, and future directions in these fields. We invite submissions that cover a broad range of topics, including, but not limited to, the following:

• Cloud architecture and infrastructure for big data;
• Advanced data analytics and machine learning in the cloud;
• Security, privacy, and compliance in cloud-based data systems;
• Optimization of cloud resources for big data processing;
• Applications of cloud computing and big data in various industries (e.g., healthcare, finance, education, smart cities);
• The role of artificial intelligence in enhancing cloud and big data solutions;
• Case studies and real-world implementations of cloud and big data technologies.

This Special Issue aims to bring together researchers, practitioners, and industry experts to share their knowledge and experiences, fostering collaboration and innovation in the development of cloud computing and big data solutions. By addressing the challenges and opportunities in these fields, this Special Issue will contribute to the advancement of technology and its application in solving complex problems in the modern world.

We look forward to receiving your valuable contributions to this Special Issue, and to advancing the discourse on the critical intersection of cloud computing and big data.

Dr. Yu-Wei Chan
Prof. Dr. Chao-Tung Yang
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.

• big data analytics
• data security and privacy
• multi-cloud strategies
• cloud resource optimization
• machine learning
• generative AI
• cloud federation
• cloud resource management
• cloud security