Emulating Space Computing Networks with RHONE(ATC'25)

RHONE Satellite Telemetry Dataset

This repository contains the dataset released in our USENIX ATC '25 paper Emulating Space Computing Networks with RHONE. The dataset is derived from Baoyun, a 12U CubeSat of the Tiansuan constellation, which was designed and launched for scientific research. Baoyun is equipped with widely used COTS computing payloads, including Raspberry Pi 4Bs, to support experiments in real-time edge computing in space environments.To access and use this dataset, please visit the link here:https://drive.google.com/drive/folders/1-WmbssCbnM2-lAsT6gNB_d0K6ojHJrTm?usp=drive_link

🛰 Source

The dataset was collected from real in-orbit telemetry of Baoyun and spans a period of 123 days, from [2022-04-14] to [2022-07-16]. It primarily consists of power consumption traces of various satellite components. These power values are computed from raw electrical telemetry—namely voltage and current readings.

🗂 Data Overview

The dataset is organized into two categories based on the naming convention of the fields:

Platform Power Data (p_pl_ prefix)

Includes power traces from satellite platform subsystems:

• p_pl_solar1, p_pl_solar2: Power generation from the two solar panels
• p_total: Total power generated by the satellite
• p_sum_bus: Total power consumed by all onboard systems
• p_pl_magnetic_torquer: Power consumption of the magnetic torquer
• p_pl_xband: Power usage of the X-band RF communication module
• Other platform subsystems have been anonymized for confidentiality. Their numerical identifiers (e.g., p_pl_1) do not reflect physical characteristics and are purely for indexing purposes.

Payload Power Data (p_pa_ prefix)

Includes power usage of payloads:

• p_pa_raspberryPi4b: Power consumption of the Raspberry Pi 4B payload
• Other payload names have been anonymized for confidentiality. Their numerical identifiers (e.g., p_pa_03, p_pa_12) do not reflect physical characteristics and are purely for indexing purposes.

📂 Access and Format

• The dataset is released as CSV files, partitioned by date for ease of use.

🔓 License and Citation

This dataset is released under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

If you use this dataset in your work, please cite our paper:

Liying Wang, Qing Li, Yuhan Zhou, Zhaofeng Luo, Donghao Zhang, Shangguang Wang, Xuanzhe Liu, and Chenren Xu. Emulating space computing networks with RHONE. In USENIX Annual Technical Conference, USENIX ATC '25, Boston, MA, USA, 2025.