Treffer: Adaptive fault tolerance mechanisms for ensuring high availability of digital twins in distributed edge computing systems.

Title:
Adaptive fault tolerance mechanisms for ensuring high availability of digital twins in distributed edge computing systems.
Authors:
Sahu D; SCSET, Bennett University, Plot Nos 8, 11, TechZone 2, Greater Noida, Uttar Pradesh, 201310, India., Nidhi; SCSET, Bennett University, Plot Nos 8, 11, TechZone 2, Greater Noida, Uttar Pradesh, 201310, India., Prakash S; Department of Electronics and Communication, University of Allahabad, Prayag Raj, Uttar Pradesh, India. shivprakash@allduniv.ac.in., Yang T; University of South Wales, Pontypridd, UK., Rathore RS; Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, UK. rsrathore@cardiffmet.ac.uk., Wang L; Xi'an Jiaotong-Liverpool University, Suzhou, China., Sharma U; Department of Information Technology, Babu Banarasi Das Institute of Technology and Management (BBDITM), Lucknow, India., Alsolbi I; Data Science Department, College of Computing, Umm Al-Qura University, 21955, Makkah, Saudi Arabia. insolbi@uqu.edu.sa.
Source:
Scientific reports [Sci Rep] 2025 Nov 24; Vol. 15 (1), pp. 41676. Date of Electronic Publication: 2025 Nov 24.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: PubMed not MEDLINE; MEDLINE
Imprint Name(s):
Original Publication: London : Nature Publishing Group, copyright 2011-
References:
Sci Rep. 2025 Mar 23;15(1):10034. (PMID: 40122909)
Sci Rep. 2025 Jan 29;15(1):3730. (PMID: 39881204)
Sensors (Basel). 2023 May 18;23(10):. (PMID: 37430789)
Sci Rep. 2025 Aug 19;15(1):30452. (PMID: 40830214)
Sensors (Basel). 2022 Oct 14;22(20):. (PMID: 36298173)
Sci Rep. 2025 Feb 20;15(1):6266. (PMID: 39979563)
Sci Rep. 2025 Sep 30;15(1):34046. (PMID: 41028087)
Contributed Indexing:
Keywords: Adaptive fault tolerance; Digital twins; Distributed edge computing; Energy-efficient computing; High availability; Hybrid genetic-PSO algorithm; Node failure recovery; Resource reallocation; System resilience; Task migration
Entry Date(s):
Date Created: 20251125 Latest Revision: 20251128
Update Code:
20251128
PubMed Central ID:
PMC12645026
DOI:
10.1038/s41598-025-25590-4
PMID:
41286220
Database:
MEDLINE

Weitere Informationen

The increasing adoption of Digital Twins (DTs) in distributed edge computing systems necessitates robust fault tolerance mechanisms to ensure high availability and reliability. This paper presents an adaptive fault tolerance framework designed to maintain the continuous operation of DTs in dynamic and resource-constrained edge environments. The primary objective is to mitigate failures at edge nodes, minimize downtime, and ensure seamless migration of DT instances without disrupting system performance. The proposed framework integrates a novel Hybrid Genetic-PSO for Adaptive Fault Tolerance (HGPAFT) algorithm, combining the strengths of genetic algorithms and particle swarm optimization. The algorithm dynamically reallocates resources and migrates DT instances in response to node failures, utilizing real-time monitoring and predictive failure detection to enhance system resilience. A key innovation lies in the adaptive nature of the fault tolerance mechanisms, which adjust resource reallocation and task migration strategies based on the evolving conditions of the edge network, such as node load, energy constraints, and communication delays. The results, validated through extensive simulations, demonstrate significant improvements in system availability, with recovery probabilities exceeding 98% and up to 20% reductions in reallocation and migration costs compared to traditional fault tolerance mechanisms. Additionally, the proposed framework optimizes energy consumption and resource utilization, critical for sustainable edge computing. This research contributes to the state of the art by offering a scalable and energy-efficient fault tolerance solution tailored for the decentralized and heterogeneous nature of distributed edge computing, ensuring the continuous and reliable operation of Digital Twins.
(© 2025. The Author(s).)

Declarations. Competing interests: The authors declare no competing interests.