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Applied Sciences
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Advancements in Computer Systems and Operating Systems
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Advancements in Computer Systems and Operating Systems

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (30 June 2025) | Viewed by 3371

Special Issue Editor

Prof. Dr. João Durães

E-Mail Website
Guest Editor
ISEC-Coimbra Institute of Engineering, Coimbra Polytechnic, 3030-199 Coimbra, Portugal
Interests: software reliability; software engineering; dependability evaluation; fault injection

Special Issue Information

Dear Colleagues,

Computer-based systems are increasingly present in almost all aspects of modern society. From simple daily life activities to critical industrial control, everything is dependent on software running on a device, often controlled by a specifically tailored operating system. This trend is increasing, and new application scenarios are continuously being proposed. This leads to a demand for new types of operating system, which must support new features for new operational requirements, including security, power management, and device control, among many other aspects. At the same time, new applications are being put forward, addressing new types of system use, which, in turn, lead to new requirements for operating systems.

We are, therefore, interested in papers presenting advancements in topics including, but not limited to, the following:

  • Innovative approaches to addressing new security issues;
  • Novel applications of generic operating systems for new application scenarios;
  • Improvements to power management suitable for IoT and edge computing;
  • Ground-breaking new features to address emerging scenarios and operational concerns;
  • Innovative operating system features that open up new avenues for modern applications;
  • Case studies on the innovative use of computer-based systems and operating systems;
  • Systematic surveys detailing new trends and open research issues in computer systems and operating systems.

Prof. Dr. João Durães
Guest Editor

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.

Keywords

  • operating systems
  • security
  • IoT
  • edge computing
  • cloud
  • emerging computer applications

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

25 pages, 3974 KiB  
Article
The Hybrid Model: Prediction-Based Scheduling and Efficient Resource Management in a Serverless Environment
by Louai Shiekhani, Hui Wang, Wen Shi, Jiahao Liu, Yuan Qiu, Chunhua Gu and Weichao Ding
Appl. Sci. 2025, 15(14), 7632; https://doi.org/10.3390/app15147632 - 8 Jul 2025
Viewed by 565
Abstract
Serverless computing has gained significant attention in recent years. However, the cold start problem remains a major challenge, not only because of the substantial latency it introduces to function execution time, but also because frequent cold starts lead to poor resource utilization, especially [...] Read more.
Serverless computing has gained significant attention in recent years. However, the cold start problem remains a major challenge, not only because of the substantial latency it introduces to function execution time, but also because frequent cold starts lead to poor resource utilization, especially during workload fluctuations. To address these issues, we propose a multi-level scheduling solution: the Hybrid Model. This model is designed to reduce the frequency of cold starts while maximizing container utilization. At the global level (across invokers), the Hybrid Model employs a skewness-aware scheduling strategy to select the most appropriate invoker for each request. Within each invoker, we introduce a greedy buffer-aware scheduling method that leverages the available slack (remaining buffer) of warm containers to aggressively encourage their reuse. Both the global and the local schedule are tightly integrated with a prediction component- The Hybrid Predictor- that combines Auto-Regressive Integrated Moving Average ARIMA (linear trends) and Random Forest (non-linear residuals + environment-aware features) for 5-min workload forecasts. The Hybrid Model is implemented on Apache OpenWhisk and evaluated using Azure-like traces and real FaaS applications. The evaluations show that the Hybrid Model achieves up to 34% SLA violation reductions compared to three state-of-the-art approaches and maintains the container utilization to be more than 80%. Full article
(This article belongs to the Special Issue Advancements in Computer Systems and Operating Systems)
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20 pages, 867 KiB  
Article
Leveraging Static and Dynamic Wear Leveling to Prolong the Lifespan of Solid-State Drives
by Ilhoon Shin
Appl. Sci. 2024, 14(18), 8186; https://doi.org/10.3390/app14188186 - 11 Sep 2024
Cited by 1 | Viewed by 2079
Abstract
In order to extend the lifespan of SSDs, it is essential to achieve wear leveling that evenly distributes the accumulated erase counts of NAND blocks, thereby delaying the occurrence of bad blocks as much as possible. This paper proposes the Greedy-MP policy, integrating [...] Read more.
In order to extend the lifespan of SSDs, it is essential to achieve wear leveling that evenly distributes the accumulated erase counts of NAND blocks, thereby delaying the occurrence of bad blocks as much as possible. This paper proposes the Greedy-MP policy, integrating static and dynamic wear leveling. When a specific block exhibits excessive erasures surpassing a defined threshold, Greedy-MP initiates the migration of cold data, expected to undergo infrequent modifications, to that block. Additionally, migrated blocks are excluded as candidates for garbage collection until their erase counts reach a similar level to others, preventing premature transition into bad blocks. Performance evaluations demonstrate that Greedy-MP achieves the longest lifespan across all test scenarios. Compared to policies solely utilizing static wear leveling like PWL, it extends the lifespan by up to 1.72 times. Moreover, when integrated with dynamic wear leveling policies such as CB alongside static wear leveling like PWL, it extends the lifespan by up to 1.99 times. Importantly, these extensions are achieved without sacrificing performance. By preserving garbage collection efficiency, Greedy-MP delivers the shortest average response time for I/O requests. Full article
(This article belongs to the Special Issue Advancements in Computer Systems and Operating Systems)
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