Advances in Algorithm Theory and Computer Networks
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 7215
Special Issue Editors
Interests: combinatorial optimization; computer networks; algorithm theory; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: experimental algorithmics; metaheuristics; genetic algorithms; combinatorial optimization; machine learning; causal inference applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We invite you to participate in our Special Issue of Mathematics titled "Advances in Algorithm Theory and Computer Networks." This issue seeks to bridge the gap between theory and practice, highlighting the interplay between mathematics, algorithmic theory, and computer networks. Submissions should focus on novel algorithmic theories, computational frameworks, and network architectures that ensure network scalability, efficiency, and adaptability. Contributions should emphasize mathematical rigor while addressing real-world applicability.
We welcome the submission of original research and review papers on topics including, but not limited to, the following: machine learning for algorithmic challenges in networks, including the ML-driven optimization of network routing, resource allocation, and congestion control; applications of reinforcement learning, deep learning, and federated learning for adaptive network management, anomaly detection, and security in large-scale networks; information-theoretic approaches, including the theoretical limits of data transmission, compression, and storage in decentralized networks; game-theoretic models and results, including strategic decision-making in network resource allocation, security, and distributed control; equilibrium analysis for multi-agent systems and competitive network environments; distributed and centralized algorithms for NP-hard problems in networks; next-generation network architectures, including algorithms for information-centric networking (ICN), edge computing, and agentic communications; architectures supporting low latency and high-bandwidth applications (e.g., video-on-demand); the theoretical and practical challenges of future networks, including the scalability of algorithms for networks with billions of heterogeneous devices; and energy efficiency, security, and resilience in decentralized, self-organizing systems.
Prof. Dr. Rolando Menchaca-Méndez
Dr. Marcela Quiroz-Castellanos
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. 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
- algorithm theory
- computer networks
- machine learning in computer networks
- distributed combinatorial optimization
- algorithmic foundations of next-generation network architectures
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