Distributed Systems: Methods and 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: 31 October 2025 | Viewed by 1877

Special Issue Editor

Department of Computer Science, Loughborough University, Loughborough LE11 3TU, UK
Interests: algorithms; random processes; distributed systems; parallel computing; distributed algorithms; scheduling and load balancing; randomised algorithms; CS theory; storage systems
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Special Issue Information

Dear Colleagues,

We invite you to submit your latest research to our Special Issue, entitled "Distributed Systems: Methods and Applications".

Over the past five decades, distributed systems have been the subject of research, steadily growing in significance. With the expansion of the internet and networked computing and with the transition from single-core computers to parallel systems, the importance of distributed computing has reached unprecedented levels. In the design and development of efficient systems, empirical methods have their limits due to the costs and complexity involved. This amplifies the significance of modelling and analysing aspects of distributed systems, such as security or replication, theoretically and through simulations.

We welcome submissions that explore new approaches, methodologies, and applications in the field of distributed systems. Your contributions will enhance our knowledge and understanding of distributed systems, leading to more resilient and efficient systems.

Topics include, but are not limited to, the following:

  • High-performance and parallel computing;
  • Distributed algorithms and data structures;
  • Cloud, fog, and edge computing;
  • Serverless computing;
  • Microservice architectures;
  • Internet of Things;
  • Distributed operating systems;
  • Distributed storage systems;
  • Federated learning;
  • Consensus and leader election algorithms;
  • Population protocols;
  • Blockchains.

Dr. Lars Nagel
Guest Editor

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

  • distributed systems
  • distributed algorithms
  • parallel computing
  • blockchains
  • consensus and leader election algorithms
  • cloud, edge, and fog computing
  • distributed machine learning
  • federated learning
  • Internet of Things (IoT)
  • smart systems
  • microservices
  • distributed storage systems

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Published Papers (2 papers)

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Research

26 pages, 2653 KiB  
Article
Dynamic and Stochastic Models for Application Management in Distributed Computing Systems
by Saleh M. Altowaijri
Mathematics 2025, 13(4), 581; https://doi.org/10.3390/math13040581 - 10 Feb 2025
Viewed by 508
Abstract
Fog and edge computing have proven indispensable in tackling issues related to time-critical applications, high network congestion, user confidentiality, and data protection. While these emerging paradigms offer significant potential, substantial effort is required to study and design systems and applications tailored to their [...] Read more.
Fog and edge computing have proven indispensable in tackling issues related to time-critical applications, high network congestion, user confidentiality, and data protection. While these emerging paradigms offer significant potential, substantial effort is required to study and design systems and applications tailored to their unique characteristics. This study conducts a comprehensive analysis of distributed application scheduling and offloading across cloud, fog, and edge environments. We developed multiple prototypes to investigate the organization of distributed applications under various system scales and workloads. To evaluate the system’s effectiveness and reliability, we computed steady-state probabilities using enhanced Markov models specifically designed for cloud, fog, and edge settings. These probabilities were employed to establish key metrics for assessing the efficiency of distributed application scheduling and offloading, including network utilization, response delay, energy consumption, and associated costs. Full article
(This article belongs to the Special Issue Distributed Systems: Methods and Applications)
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25 pages, 4492 KiB  
Article
Resource Allocation Optimization Model for Computing Continuum
by Mihaela Mihaiu, Bogdan-Costel Mocanu, Cătălin Negru, Alina Petrescu-Niță and Florin Pop
Mathematics 2025, 13(3), 431; https://doi.org/10.3390/math13030431 - 27 Jan 2025
Viewed by 870
Abstract
The exponential growth of Internet of Things (IoT) devices has led to massive volumes of data, challenging traditional centralized processing paradigms. The cloud–edge continuum computing model has emerged as a promising solution to address this challenge, offering a distributed approach to data processing [...] Read more.
The exponential growth of Internet of Things (IoT) devices has led to massive volumes of data, challenging traditional centralized processing paradigms. The cloud–edge continuum computing model has emerged as a promising solution to address this challenge, offering a distributed approach to data processing and management and improved performances in terms of the overhead and latency of the communication network. In this paper, we present a novel resource allocation optimization solution in cloud–edge continuum architectures designed to support multiple heterogeneous mobile clients that run a set of applications in a 5G-enabled environment. Our approach is structured across three layers, mist, edge, and cloud, and introduces a set of innovative resource allocation models that addresses the limitations of the traditional bin-packing optimization problem in IoT systems. The proposed solution integrates task offloading and resource allocation strategies designed to optimize energy consumption while ensuring compliance with Service Level Agreements (SLAs) by minimizing resource consumption. The evaluation of our proposed solution shows a longer period of active time for edge servers because of the lower energy consumption. These results indicate that the proposed solution is viable and a sustainability model that prioritizes energy efficiency in alignment with current climate concerns. Full article
(This article belongs to the Special Issue Distributed Systems: Methods and Applications)
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