Application of Proportional-Share with Punishment Principle for Resource Sharing in Parallel Computing Applications

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 13 | 01 | Page :
    By

    Manas Kumar Yogi,

  1. Assistant, Professor, Department of CSE, Pragati Engineering College (A), Surampalem, Andhra Pradesh, India

Abstract

Efficient resource sharing is a cornerstone of high-performance parallel computing. While proportional-share scheduling has long been a foundational approach for distributing resources according to predefined weights, its effectiveness can be compromised by tasks that over-consume their allocated share, leading to system-wide performance degradation and unfairness. This review article investigates the application of the “Proportional-Share with Punishment” (PSWP) principle, a hybrid scheduling paradigm designed to address this challenge. PSWP integrates the flexibility of proportional sharing with a robust penalty mechanism that dynamically corrects for resource over-consumption, ensuring long-term fairness and stability. This article thoroughly synthesizes various recent scholarly work from 2020–2026 to provide a comprehensive overview of the PSWP principle, its theoretical underpinnings, and its practical implementations in parallel computing platforms, cloud platforms, and distributed systems. We explore the various forms of punishment mechanisms, their triggers, and their impact on system performance metrics like throughput, latency, and fairness. Furthermore, we examine the challenges associated with implementing PSWP, including the overhead of monitoring and the potential for unintended consequences.

Keywords: Big data, cluster, distributed, high performance computing, resource

How to cite this article:
Manas Kumar Yogi. Application of Proportional-Share with Punishment Principle for Resource Sharing in Parallel Computing Applications. Recent Trends in Parallel Computing. 2026; 13(01):-.
How to cite this URL:
Manas Kumar Yogi. Application of Proportional-Share with Punishment Principle for Resource Sharing in Parallel Computing Applications. Recent Trends in Parallel Computing. 2026; 13(01):-. Available from: https://journals.stmjournals.com/rtpc/article=2026/view=237661


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Ahead of Print Subscription Review Article
Volume 13
01
Received 16/01/2026
Accepted 21/01/2026
Published 26/02/2026
Publication Time 41 Days
68

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