doi: 10.18178/ijfcc.2026.15.2.635
An IaC-based Large-scale BACnet Emulation Platform
- 1 Graduate School of Kanazawa Institute of Technology, Nonoichi, Japan
- 2 Department of Electronics and Information Systems Engineering, Kanazawa Institute of Technology, Nonoichi, Japan
- Manuscript received May 12, 2025
- accepted August 3, 2025
- published October 12, 2026
Abstract
Integrating Building Automation Systems (BAS) into Cyber-Physical Systems (CPS) introduces critical challenges in scalability: as network scale grows, traffic characteristics shift and resource consumption increases in ways that are difficult to anticipate. Existing BACnet validation tools, however, focus primarily on single-device conformance testing and lack the means to automatically construct large-scale, realistic network environments with reproducibility. This paper proposes a large-scale BACnet emulation platform that integrates hypervisor-level input emulation with Infrastructure as Code (IaC). By injecting HID events through the QEMU/libvirt stack, the platform enables control of unmodified application binaries without any dependency on guest OS type or security policy. Declarative configuration via Ansible allows network topology and node configuration to be defined as code and instantiated on demand, ensuring reproducible test scenarios across heterogeneous environments. The proposed platform facilitates traffic analysis in configurations where real and virtual BACnet applications coexist, and contributes to seamless CPS integration that preserves and leverages existing BACnet infrastructure.
Keywords
- BACnet
- infrastructure as code
- network emulation
- cyber-physical systems
- scalability
- QEMU libvirt
How to Cite
Yuki Hatanaka and Tetsuya Yokotani, "An IaC-based Large-scale BACnet Emulation Platform," International Journal of Future Computer and Communication, vol. 15, no. 2, pp. 69-73, 2026. https://doi.org/ 10.18178/ijfcc.2026.15.2.635
Copyright & License
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).




