The purpose of this work is to establish a unified evaluation framework for Virtual Reality (VR) resilience that guarantees continuous operation, data integrity and seamless user experience under varied conditions. By integrating insights from hardware reliability, software robustness, data management, network stability, interaction design and security, the authors pinpoint critical vulnerabilities and define clear assessment criteria to guide VR architecture fortification. The authors survey leading resilience techniques across six domains. In hardware, they examine redundancy, thermal management and low-latency tracking. Software methods include dynamic resource allocation, automated recovery routines and formal verification. Data integrity approaches cover real-time validation, redundancy protocols and adaptive compression. Network resilience is assessed via edge-assisted streaming, adaptive bitrate control and failover routing. Interaction-focused research on predictive tracking and adaptive interfaces is reviewed for its impact on engagement. Security measures such as multi-factor authentication, end-to-end encryption and AI-driven threat detection are evaluated alongside emerging quantum cryptography and hybrid cloud-edge architectures. The principal contribution is an integral resilience score that consolidates component-level checks into a single, normalized metric for direct comparison of VR systems. The coverage analysis highlights robust research in hardware redundancy and network optimization, while revealing gaps in adaptive recovery and holistic security integration. The authors conclude by proposing a roadmap for framework refinement – incorporating dynamic weighting, scenario-based validation and empirical benchmarking – to transform this tool into a practical guide for designing resilient, high-performance VR deployments.

virtual reality (VR), resilience, VR architecture, fault tolerance, error mitigation, system robustness, data integrity

Full Text:

PDF

1. Abdlkarim, B., de Rosario, H., Ramon, T., Ivorra, A., & Hossny, M. (2024). A methodological framework to assess the accuracy of virtual reality hand-tracking systems: A case study with the Meta Quest 2. Behavior Research Methods, 56, 1052–1063. https://doi.org/10.3758/s13428-022-02051-8

2. Aldea, L., Bocu, R., & Solca, R. N. (2023). Real-time monitoring and management of hardware and software resources in heterogeneous computer networks through an integrated system architecture. Symmetry, 15(6). https://doi.org/10.3390/sym15061134

3. Chaccour, C., Boulogeorgos, A.-A. A., Saad, W., & Bennis, M. (2019). On the reliability of wireless virtual reality at terahertz (THz) frequencies. In 2019 10th IFIP International Conference on New Technologies, Mobility and Security (NTMS) (pp. 1–5). IEEE. https://doi.org/10.1109/NTMS.2019.8763780

4. Dastgerdy, S. K. (2024). Virtual reality and augmented reality security: A reconnaissance and vulnerability assessment approach. arXiv. https://doi.org/10.48550/arXiv.2407.15984

5. Fengting, L., & Kyongmin, L. (2025). The impact of perceived usefulness, ease of use, trust, and usage attitude on the intention to maintain engagement in AR/VR sports: An exploration of the technology acceptance framework. Journal of Asian Scientific Research, 15(1), 1–10.

6. Kachur, A., Lysenko, S., Bodnaruk, O., & Gaj, P. (2024). Methods of improving security and resilience of VR systems’ architecture. In Proceedings of the 5th International Workshop on Intelligent Information Technologies and Systems of Information Security (IntelITSIS 2024).

7. Kashtalian, A., Lysenko, S., Savenko, O., Nicheporuk, A., Sochor, T., & Avsiyevych, V. (2024). Multi- computer malware detection systems with metamorphic functionality. Radioelectronic and Computer Systems, (1), 152–175. https://doi.org/10.32620/reks.2024.1.13

8. Kojić, T., Malaka, R., Novak, D., Wiemeyer, J., & Göbel, S. (2023). Effects of user factors on user experience in virtual reality: Age, gender, and VR experience as influencing factors for VR exergames. Quality and User Experience, 8(1). https://doi.org/10.1007/s41233-023-00056-5

9. Kraus, K., Reichert, R., & Schedel, J. (2025). VR-based workplace training and spaces of learning: A social space study of VR training for apprentice electricians. International Journal for Research in Vocational Education and Training, 12(2), 151–173.

10. Laranjeiro, N., Angelo, J., & Bernardino, J. (2021). A systematic review on software robustness assessment. ACM Computing Surveys (CSUR), 54(4), 1–65. https://doi.org/10.1145/3448977

11. Li, Y., Ch’ng, E., & Cobb, S. (2023). Factors influencing engagement in hybrid virtual and augmented reality. ACM Transactions on Computer-Human Interaction, 30(4). https://doi.org/10.1145/3589952

12. Lysenko, S., & Kachur, A. (2023). Challenges towards VR technology: VR architecture optimization. In 2023 13th International Conference on Dependable Systems, Services and Technologies (DESSERT). IEEE. https://doi.org/10.1109/DESSERT61349.2023.10416538

13. Lysenko, S., Savenko, O., Bobrovnikova, K. (2018). DDoS botnet detection technique based on the use of the semi-supervised fuzzy c-means clustering. In CEUR Workshop Proceedings, 2104, 688–695.

14. Lysenko, S., Savenko, O., Bobrovnikova, K., Kryshchuk, A., & Savenko, B. (2017). Information technology for botnets detection based on their behaviour in the corporate area network. In Communications in Computer and Information Science, 718, 166–181.

15. Merino, J., Xie, X., Parlikad, A., Lewis, I., & McFarlane, D. (2020). Impact of data quality in real-time big data systems. In ER Forum, Demo and Posters 2020 co-located with the 39th International Conference on Conceptual Modeling (ER 2020). https://doi.org/10.17863/CAM.59426

16. Moreno-Lumberas, D., Ramos, M., Hernández, J., & Vargas, A. (2024). Software development metrics: To VR or not to VR. Empirical Software Engineering. https://doi.org/10.1007/s10664-023-10435-3

17. Ndjama, J. D. J. N., & Van Der Westhuizen, J. (2025). A systematic review of the challenges and limitations of VR in education. In Creating Immersive Learning Experiences Through Virtual Reality (VR) (pp. 1–32).

18. Phung, V., & Jukan, A. (2022). Increasing fault tolerance and throughput with adaptive control plane in smart factories. arXiv. https://doi.org/10.48550/arXiv.2205.13057

19. Prakash, S., & Vyas, V. (2022). Analysis of fault tolerance techniques in virtual machine environment. In ICT Analysis and Applications. https://doi.org/10.1007/978-981-16-5655-2_12

20. Sansone, L. G., Gonzalez, J., Berton, A., & Soranzo, A. (2022). Robustness and static-positional accuracy of the SteamVR 1.0 virtual reality tracking system. Virtual Reality, 26, 903–924. https://doi.org/10.1007/s10055-021-00584-5

21. Savenko, O., Sachenko, A., Lysenko, S., Markowsky, G., & Vasylkiv, N. (2020). Botnet detection approach based on the distributed systems. International Journal of Computing, 19(2), 190–198. https://doi.org/10.47839/ijc.19.2.1761

22. Singha, R., & Singha, S. (2025). Use of virtual reality (VR) and AI in therapeutic settings. In Transforming Neuropsychology and Cognitive Psychology with AI and Machine Learning (pp. 367–394). IGI Global Scientific Publishing.

23. Stadtmann, H. P., Mahalingam, S., & Rasheed, A. (2023). Data integration framework for virtual reality enabled digital twins. In 2023 IEEE 9th World Forum on Internet of Things. IEEE. https://doi.org/10.1109/WF-IoT58464.2023.10539546

24. Tripathi, R. D., Lyu, M., & Sivaraman, V. (2024). Assessing the impact of network quality-of-service on metaverse virtual reality user experience. In 2024 IEEE International Conference on Metaverse Computing, Networking, and Applications (MetaCom). IEEE. https://doi.org/10.1109/MetaCom62920.2024.00042.

25. Viswanathan, K., & Yazdinejad, A. (2022). Security considerations for virtual reality systems. arXiv. https://doi.org/10.48550/arXiv.2201.02563

26. Yang, Y., Zhong, L., Li, S., & Yu, A. (2023). Research on the perceived quality of virtual reality headsets in human–computer interaction. Sensors, 23, 6824. https://doi.org/10.3390/s23156824

27. Samotyi V., & Dzelendzyak U. (2018). The security and privacy problems of augmented reality technologies. Bulletin of Lviv State University of Life Safety, 17, 2018.

28. Batiuk, A. Ye., & Kulyk, Yu. R. (2024). Integration of cloud technologies into virtual reality. Ukrainian Journal of Information Tecnology, 6(1), 109–119. https://doi.org/10.23939/ujit2024.01.109.