Hybrid Graceful QoS Degradation in Distributed Operating Systems

Year : 2025 | Volume : 12 | Issue : 02 | Page : 01 07
    By

    K.V.V. Subba Rao,

  • Manas Kumar Yogi,

  1. Assistant Professor, Computer Science and Engineering Department, Pragati Engineering College (A), Surampalem, Andhra Pradesh, India
  2. Assistant Professor, Computer Science and Engineering Department, Pragati Engineering College (A), Surampalem, Andhra Pradesh, India

Abstract

Maintaining Quality of Service (QoS) in distributed operating systems is a critical challenge, especially in dynamic and resource-constrained environments. Traditional QoS mechanisms often fail to adapt effectively to unforeseen failures or load spikes, leading to abrupt service disruptions. This study reviews the concept of hybrid graceful QoS degradation, a paradigm that combines multiple strategies to ensure continuous, albeit potentially reduced, service availability. By intelligently integrating techniques like resource reservation, priority-based scheduling, adaptive algorithms, and layered QoS, distributed systems can dynamically adjust their performance in response to changing conditions. This review analyses the various techniques used in hybrid approaches, evaluates their strengths and weaknesses, and discusses the challenges associated with their implementation. We explore the importance of effective monitoring, decision-making, and communication protocols for successful degradation. Furthermore, this study identifies emerging research directions, including AI-driven QoS management and edge computing integration, highlighting the on-going evolution of QoS strategies in distributed environments. This review underscores the significance of hybrid graceful degradation in building resilient and user-friendly distributed systems.

Keywords: QoS, adaptive, dynamic, distributed, degradation, performance

[This article belongs to Journal of Operating Systems Development & Trends ]

How to cite this article:
K.V.V. Subba Rao, Manas Kumar Yogi. Hybrid Graceful QoS Degradation in Distributed Operating Systems. Journal of Operating Systems Development & Trends. 2025; 12(02):01-07.
How to cite this URL:
K.V.V. Subba Rao, Manas Kumar Yogi. Hybrid Graceful QoS Degradation in Distributed Operating Systems. Journal of Operating Systems Development & Trends. 2025; 12(02):01-07. Available from: https://journals.stmjournals.com/joosdt/article=2025/view=236507


References

  1. Hoseiny Farahabady MR, Taheri J, Zomaya AY, Tari Z. Graceful performance degradation in Apache storm. In International Conference on Parallel and Distributed Computing: Applications and Technologies. Cham: Springer International Publishing; 2020 Dec 28; 389–400.
  2. Zou J, Dai X, McDermid JA. Context-aware graceful degradation for mixed-criticality scheduling in autonomous systems. IEEE Trans Comput-Aided Des Integr Circuit Syst. 2023 Nov 7; 43(3): 788–801.
  3. Hanafy WA, Wu L, Abdelzaher T, Diggavi S, Shenoy P. Failure-Resilient ML Inference at the Edge through Graceful Service Degradation. In MILCOM 2023-2023 IEEE Military Communications Conference (MILCOM). 2023 Oct 30; 144–149.
  4. Agrawal K, Abdu Jyothi S. Cooperative Graceful Degradation in Containerized Clouds. In Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems. 2025 Mar 30; 1: 214–232.
  5. Schmidt Robert. Dependable and energy-efficient cyber-physical systems by graceful degradation. Dissertation. Germany: Universität Bremen; 2022.
  6. Zhang YW, Zheng H, Gu Z. Energy-aware adaptive mixed-criticality scheduling with semi-clairvoyance and graceful degradation. ACM Trans Embed Comput Syst. 2024 Jan 10; 23(1): 1–20.
  7. Zhang YW, Zheng H, Gu Z. EDF-based energy-efficient semi-clairvoyant scheduling with graceful degradation. IEEE Trans Comput-Aided Des Integr Circuit Syst. 2023 Oct 3; 43(2): 468–79.
  8. Boban M, Giordani M, Zorzi M. Predictive quality of service: The next frontier for fully autonomous systems. IEEE Netw. 2022 Jan 20; 35(6): 104–10.
  9. Chen F. System Support for Environmentally Sustainable Computing in Data Centers. In 2024 IEEE Computer Society Annual Symposium on VLSI (ISVLSI). 2024 Jul 1; 490–495.
  10. Seki Y, Tanigawa Y, Hirota Y, Tode H. Core and spectrum allocation to achieve graceful degradation of inter-core crosstalk with generalized hierarchical core prioritization on space-division multiplexing elastic optical networks. J Opt Commun Netw. 2022 Dec 21; 15(1): 43–56.
  11. Zhu J, Hu C, Wo T, Yu X. ScaleReactor: A graceful performance isolation agent with interference detection and investigation for container‐based scale‐out workloads. Concurr Comput: Pract Exp. 2022 Feb 15; 34(4): e6666.
  12. Boban M, Giordani M, Zorzi M. Predictive quality of service (pqos): The next frontier for fully autonomous systems. arXiv preprint arXiv:2109.09376. 2021 Sep 20.
  13. Mason F, Drago M, Zugno T, Giordani M, Boban M, Zorzi M. A reinforcement learning framework for pqos in a teleoperated driving scenario. In 2022 IEEE Wireless Communications and Networking Conference (WCNC). 2022 Apr 10; 114–119.
  14. Laidig R, Dürr F, Rothermel K, Wildhagen S, Allgöwer F. Dynamic Deterministic Quality of Service Model with Behavior-Adaptive Latency Bounds. In 2023 IEEE 29th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA). 2023 Aug 30; 127–136.
  15. Zhang J, Rong Y, Cao J, Rong C, Bian J, Wu W. DBFT: A Byzantine fault tolerance protocol with graceful performance degradation. IEEE Trans Dependable Secure Comput. 2021 Jul 8; 19(5): 3387–400.

Regular Issue Subscription Review Article
Volume 12
Issue 02
Received 28/02/2025
Accepted 07/03/2025
Published 23/07/2025
Publication Time 145 Days


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