ACC
Architecture Design and Performance Optimization of a Large-scale Online Simulation Platform for Business Decision-making
TOTAL VIEWS: 212
Abstract
This study presents a systematic investigation into the architectural design and performance optimization of a large-scale online simulation platform tailored for business decision-making. Targeting scenarios such as supply chain simulation, market forecasting, and strategic evaluation, the platform addresses the growing demands for high concurrency and real-time computational feedback. A distributed computing and microservices-based system framework was developed, integrating task decomposition, asynchronous communication, and multi-level caching to support efficient multi-node simulation management and parallel processing. A dynamic weight-based scheduling algorithm was introduced to optimize load balancing and node resource utilization. Performance tests conducted under typical business workloads demonstrated the platform’s robustness and scalability in handling large-scale concurrent tasks, elastic resource scaling, and low-latency responses. Results confirm the platform’s capability to meet the requirements of complex simulation tasks in enterprise environments, providing a reliable, efficient, and extensible technical foundation for intelligent decision-making applications.
Keywords
Business decision-making; Online simulation platform; Architecture design; Performance optimization; Distributed computing
References
[1] Olatunbosun A, Obozokhai IL, Balogun OI, et al. AI Literacy in Business: Preparing Executives for Augmented Decision-Making. J Econ Trade. 2025:150-62.
[2] Yongjin L. Architecture Design and Optimization of Large-scale Data Processing Systems in Cloud Computing Environments. Adv Comput Signals Syst. 2024;8(3).
DOI:10.23977/ACSS.2024.080313.
[3] Goran M, Alexey T, Jim B, et al. Large-scale agent-based simulations of online social networks. Auton Agent Multi-Agent Syst. 2022;36(2). DOI:10.1007/s10458-022-09565-7.
[4] YJ L, BS A, E C, et al. The McGill World Restart a Heart 2020 Campaign: a student-led, patient-engaged, large-scale online simulation program. Eur Heart J. 2021;42(Supplement1).
DOI:10.1093/eurheartj/ehab724.3144.
[5] Ryczko K, Domurad A, Buhagiar N, et al. Hashkat: large-scale simulations of online social networks. Soc Netw Anal Min. 2017;7(1):1-13. DOI:10.1007/s13278-017-0424-7.
[6] Thompson ER, Colombi MJ, Black J, et al. Disaggregated Space System Concept Optimization: Model‐Based Conceptual Design Methods. Syst Eng. 2015;18(6):549-67. DOI:10.1002/sys.21310.
[7] Cross LP, Mulford M. Realizing collaborative systems design for missile seekers by combining design margin analysis with multi-disciplinary optimization. Conc Eng. 2015;23(3):226-35. DOI:10.1177/1063293X15586837.
[8] Zhang J, Pu X. Research on Virtual Laboratory Platform Architecture Design Based on Internet. In: Proceedings of the 2016 International Conference on [Conference Name]; [Date of Conference]; [Location of Conference]. 2016.
How to cite this paper
Architecture Design and Performance Optimization of a Large-scale Online Simulation Platform for Business Decision-making
How to cite this paper: Yiting Hong. (2025) Architecture Design and Performance Optimization of a Large-scale Online Simulation Platform for Business Decision-making. Advances in Computer and Communication, 6(4), 230-235.
DOI: http://dx.doi.org/10.26855/acc.2025.10.013
More Articles
- Analysis of Implementation Pathways for Generative AI in Cross-language Code Migration and Compatibility Testing
- Research on Intelligent Marketing Strategy Optimization Based on Generative AI and User Behavior Prediction
- Research on the Application of Sentiment Analysis in Customer Segmentation and Precision Marketing
- Research on Implementation Pathways of AI-assisted Decision-making in Data Platform Architecture Optimization
- Architecture Design and Performance Optimization of a Large-scale Online Simulation Platform for Business Decision-making
- Research on Elastic Service Scaling Methods for Generative AI Applications Under Cloud-native Architectures