[论文解读] Constellation: The Autonomous Control and Data Acquisition System for Dynamic Experimental Setups

Simon Spannagel, Stephan Lachnit+14 more|arXiv (Cornell University)|Jan 10, 2026

Spacecraft Design and Technology被引用 0

一句话总结

Constellation 是一个灵活、去中心化的控制与数据采集框架，用于实验室和光束线实验，支持自治卫星、无缝设备集成，以及无需中央服务器的网络分布式运行。

ABSTRACT

The operation of instruments and detectors in laboratory or beamline environments presents a complex challenge, requiring stable operation of multiple concurrent devices, often controlled by separate hardware and software solutions. These environments frequently undergo modifications, such as the inclusion of different auxiliary devices depending on the experiment or facility, adding further complexity. The successful management of such dynamic configurations demands a flexible and robust system capable of controlling data acquisition, monitoring experimental setups, enabling seamless reconfiguration, and integrating new devices with limited effort. This paper presents Constellation, a flexible and network-distributed control and data acquisition software framework tailored to laboratory and beamline environments, that addresses the limitations of existing solutions. The framework is designed with a focus on extensibility, providing a streamlined interface for instrument integration. It supports efficient system setup via network discovery mechanisms, promotes stability through autonomous operational features, and provides comprehensive documentation and supporting tools for operators and application developers such as controllers and logging interfaces. At the core of the architectural design is the autonomy of the individual components, called satellites, which can make independent decisions about their operation and communicate these decisions to other components. This paper introduces the design principles and framework architecture of Constellation, presents the available graphical user interfaces, shares insights from initial successful deployments, and provides an outlook on future developments and applications.

研究动机与目标

• Identify a flexible framework suitable for laboratory and beamline experiment control and data acquisition.
• Enable rapid integration of new instruments with minimal effort.
• Provide autonomous, decentralized operation to manage dynamic configurations.
• Offer network discovery, robust data transmission, and comprehensive operator tooling.

提出的方法

• Develop a decentralized architecture where components (satellites) operate autonomously and communicate via defined protocols.
• Use RFC-style protocol documents to ensure interoperable implementations in C++ and Python.
• Leverage existing open-source libraries (ZeroMQ, MsgPack) for reliable networking and serialization.
• Implement network discovery (CHIRP), heartbeat monitoring (CHP), control commands (CSCP), data transmission (CDTP), and logging/telemetry (CMDP).
• Adopt hackathon-style collaborative development, continuous integration, and documentation practices to guide design and adoption.

Figure 1 : Screenshot of the Constellation GitLab Continuous Integration (CI) / Continuous Deployment pipeline for a release version. Building, formatting and documentation generation run in parallel, while testing, linting and deployment depend on a successful build.

实验结果

研究问题

• RQ1 How can a decentralized, satellite-based framework achieve reliable coordination without a central server?
• RQ2 What protocols and architectures best support dynamic instrument integration and autonomous decision-making in laboratory/beamline environments?
• RQ3 How can data transmission and monitoring be efficiently scaled in a network-distributed control system?
• RQ4 What mechanisms ensure safe operation, failure handling, and state transitions in autonomous satellites?

主要发现

• Constellation provides a decentralized network where satellites autonomously decide on operations and communicate state changes.
• The framework uses five core protocols (CHIRP, CHP, CSCP, CDTP, CMDP) built on TCP/IP with ZeroMQ and MsgPack for interoperability across C++ and Python.
• Continuous integration and documentation yield over 85% combined test coverage for core libraries and enable automated releases to PyPI, Flatpak, and tarballs.
• First applications demonstrated in DESY II testbeam, CERN SPS North Area, spent nuclear fuel characterization, and MADMAX cryostat monitoring, showing practical deployments and real-world utility.
• Throughput benchmarking on a 10G link indicates data transfer scales with record size and allocator performance, approaching link bandwidth for larger records.
• The system emphasizes user-driven requirements, with RFC-style protocol documents enabling parallel, independent implementations and straightforward instrument integration.

Figure 2 : Sequence diagram for Constellation Host Identification & Reconnaissance Protocol (CHIRP) showing the message flow between an already running satellite (B) and a newly started satellite (A). Satellite A offers a service and requests a service from others. Satellite B answers the request, a