Theoretical Foundations and Algorithms for Scheduling in Parallel and Distributed Systems
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information and Communications Technology".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 871
Special Issue Editors
Interests: parallel and distributing computing; scheduling algorithms; complexity and approximation; transactional memory; robotics; internet of things; blockchain; fault-tolerance
Interests: distributed systems; deep learning; cloud computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Efficient scheduling is a fundamental challenge in parallel and distributed computing, directly impacting system performance, scalability, and resource utilization. As computing environments evolve from traditional multiprocessors and clusters to heterogeneous systems, cloud infrastructures, and large-scale distributed systems, scheduling problems have become increasingly complex. These challenges arise from the heterogeneity of workloads, dynamic resource availability, communication overheads, and strict requirements on performance and energy efficiency.
Theoretical foundations provide the mathematical models and complexity analyses that guide the design and evaluation of scheduling strategies in distributed systems. Building on this foundation, algorithmic advances offer practical solutions that balance optimality with scalability, often addressing NP-hard problems through approximation, heuristics, and randomized methods. Recent developments also incorporate machine learning, game theory, and stochastic modeling to adapt scheduling decisions to uncertain, real-world environments.
This Special Issue brings together contributions that advance both the theoretical underpinnings and algorithmic techniques for solving scheduling problems in parallel and distributed systems. We invite submissions that explore innovative theories, models, algorithms, and applications in scheduling for parallel and distributed systems. Topics of interest include, but are not limited to, the following:
- Complexity analysis and performance bounds of scheduling problems;
- Approximation, heuristic, and randomized algorithms;
- Task allocation and load balancing in parallel and distributed systems;
- Scheduling under uncertainty, dynamic environments, or heterogeneous resources;
- Energy-aware and performance-driven scheduling strategies;
- Models and algorithms for fog, cloud, and edge computing;
- Machine learning and data-driven approaches to scheduling;
- Applications of scheduling algorithms in emerging technologies such as IoT and Blockchain.
Dr. Pavan Poudel
Prof. Dr. Long Cheng
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 250 words) can be sent to the Editorial Office for assessment.
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. Information is an international peer-reviewed open access monthly 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 1800 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
- parallel and distributed computing
- distributed systems
- scheduling algorithms
- approximation algorithms
- transactional memory
- load balancing
- task allocation
- resource management
- complexity analysis
- heterogeneous systems
- cloud computing
- edge computing
- blockchain
- iot
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