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Performability Analysis for Large-Scale Multi-State Computing Systems: Methodologies, Advances, and Future Directions
Review Article | Published: 31 October 2025
ICCK Transactions on Systems Safety and Reliability Volume 1, Issue 2, 2025: 81-97
Volume 1, Issue 2, ICCK Transactions on Systems Safety and Reliability
Volume 1, Issue 2, 2025
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ICCK Transactions on Systems Safety and Reliability, Volume 1, Issue 2, 2025: 81-97

Free to Read | Review Article | 31 October 2025
Performability Analysis for Large-Scale Multi-State Computing Systems: Methodologies, Advances, and Future Directions
by
Yuchang Mo Yuchang Mo 1 *
Yuan Fan Yuan Fan 2
Chunyu Miao Chunyu Miao 2
Mirlan Chynybaev Mirlan Chynybaev 3
Faer Gui Faer Gui 4
Rengui Zhang Rengui Zhang 5
Jianyong Hu Jianyong Hu 6
Jinbin Mu Jinbin Mu 7
Akylbek Chymyrov Akylbek Chymyrov 3
1 School of Computer Science and Technology, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
2 Hangzhou Anheng Information Technology Co., Ltd., Hangzhou 310051, China
3 Razzakov Kyrgyz State Technical University, Bishkek 720044, Kyrgyzstan
4 Zhejiang Keepsoft Information Technology Corp.,Ltd., Hangzhou 310051, China
5 Zhejiang YuGong Information Technology Co., Ltd., Hangzhou 310002, China
6 Engineering Research Center of Digital Twin Basin of Zhejiang Province, Hangzhou 310018, China
7 Zhejiang Institute of Hydraulics and Estuary, Hangzhou 310020, China
* Corresponding Author: Yuchang Mo, [email protected]
DOI: 10.62762/TSSR.2025.527003
Received: 09 September 2025, Accepted: 26 September 2025, Published: 31 October 2025  
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Abstract
Large-scale computing systems, such as cloud data centers, grid infrastructures, and high-performance computing clusters, are the backbone of modern information technology ecosystems. These systems typically consist of numerous heterogeneous, multi-state computing nodes that exhibit varying performance levels due to component failures, degradation, or dynamic resource allocation. Performability analysis, which integrates both system reliability and performance evaluations to quantify the probability of the system operating at a specified performance level, is critical for ensuring the efficient, reliable, and cost-effective operation of these complex systems. This paper presents a comprehensive review of recent advancements in performability analysis for large-scale multi-state computing systems over the past decade. It classifies existing research into three core methodological categories: binary decision diagram (BDD)-based approaches, multi-valued decision diagram (MDD)-based approaches, and comparative benchmarking with traditional methods (e.g., continuous-time Markov chains (CTMC), universal generating function (UGF)). For each category, the paper details key methodologies, algorithmic innovations, and practical applications. Additionally, the promising future directions are proposed to address emerging challenges, such as handling dynamic system behaviors, integrating real-time data, and optimizing resource allocation for performability. This review provides a valuable reference for researchers, system designers, and operators seeking to enhance the performability of large-scale computing systems and mitigate risks associated with service level agreement (SLA) violations.
Graphical Abstract
Performability Analysis for Large-Scale Multi-State Computing Systems: Methodologies, Advances, and Future Directions
Keywords
performability analysis
large-scale computing systems
multi-state systems
binary decision diagrams (BDD)
multi-valued decision diagrams (MDD)
reliability
system performance
Data Availability Statement
Not applicable.
Funding
This work was supported without any funding.
Conflicts of Interest
Yuan Fan and Chunyu Miao are employees of Hangzhou Anheng Information Technology Co., Ltd., Hangzhou 310051, China; Faer Gui is an employee of Zhejiang Keepsoft Information Technology Corp.,Ltd., Hangzhou 310051, China; Rengui Zhang is an employee of Zhejiang YuGong Information Technology Co., Ltd., Hangzhou 310002, China; Jianyong Hu is an employee of Engineering Research Center of Digital Twin Basin of Zhejiang Province, Hangzhou 310018, China; Jinbin Mu is an employee of Zhejiang Institute of Hydraulics and Estuary, Hangzhou 310020, China.
Ethical Approval and Consent to Participate
Not applicable.
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Cite This Article
APA Style
Mo, Y., Fan, Y., Miao, C., Chynybaev, M., Gui, F., Zhang, R., Hu, J., Mu, J. & Chymyrov, A. (2025). Performability Analysis for Large-Scale Multi-State Computing Systems: Methodologies, Advances, and Future Directions. ICCK Transactions on Systems Safety and Reliability, 1(2), 81–97. https://doi.org/10.62762/TSSR.2025.527003
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