Advanced Data Science Technology for the Safety, Reliability, and Economic Viability of Sustainable Distributed Systems and Complex Industrial Systems
A special issue of Sustainability (ISSN 2071-1050).
Deadline for manuscript submissions: 31 August 2026 | Viewed by 36
Special Issue Editors
Interests: network security; cryptography applications; AI for security
Interests: system reliability modeling and optimization decision; stochastic modeling; energy digital economy; operation research optimization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid advancement of data science technologies has significantly impacted the safety, reliability, and economic efficiency of sustainable distributed systems and complex industrial systems. These systems are critical to modern infrastructure, ranging from energy grids to manufacturing processes, and their optimization is essential for achieving sustainability goals. This Special Issue aims to explore the intersection between advanced data science techniques and the challenges of maintaining safety, reliability, and economic viability in these systems. By leveraging cutting-edge methodologies such as machine learning, stochastic modeling, and optimization algorithms, this Special Issue seeks to address key issues in system reliability, energy efficiency, and cybersecurity, among others.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- AI and machine learning applications in industrial systems;
- Cybersecurity and data integrity in distributed systems;
- Energy efficiency and the digital economy in industrial processes;
- System reliability modeling and optimization;
- Stochastic modeling for sustainable systems;
- Predictive maintenance and fault detection using data science;
- Optimization algorithms for resource allocation in complex systems;
- Case studies on the implementation of data science into real-world industrial and distributed systems.
We look forward to receiving your original research articles and reviews, which will contribute to advancing the field of sustainable distributed and industrial systems through the lens of data science.
Prof. Dr. Hua Zhang
Dr. Hongda Gao
Dr. Tengfei Tu
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. Sustainability 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
- data science
- sustainable systems
- industrial systems
- system reliability
- machine learning
- cybersecurity
- energy efficiency
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