VISTA: A Benchmark for Real-Time Video Streaming under Network Impairments in Surgical Teleoperation
Zexin Deng, Zhenhui Yuan, Tian Lu, Gaofeng Li, Meipeng Huang, Longhao Zou
- Year
- 2026
- Access
- Open access
Abstract
Real-time video streaming is crucial in surgical teleoperation, yet reproducible evaluation under realistic network impairments remains limited. This paper presents VISTA, a benchmark designed to study how impairments along the forward video path affect received video quality, temporal continuity, and human task performance. VISTA employs Linux Traffic Control with NetEm and a Gilbert-Elliott loss model to emulate five network conditions: Hospital LAN, 5G Urban, 4G Rural, LEO Satellite, and GEO Satellite. The benchmark integrates a standardised peg transfer task with synchronized measurements of network quality of service (QoS), objective video quality (PSNR, SSIM, and VMAF), and temporal continuity through freeze rate, while maintaining a stable reverse control channel. Across 375 experimental trials, network degradation substantially reduced teleoperation performance: success rate decreased from 97% in Hospital LAN to 79% in 5G Urban, 35% in 4G Rural, 71% in LEO Satellite, and 12% in GEO Satellite, while mean task completion time for successful trials increased from 80 s in Hospital LAN to 117 s in 5G Urban, 211 s in 4G Rural, 152 s in LEO Satellite, and 255 s in GEO Satellite. These findings show that network impairments have a direct impact on task completion and success in surgical teleoperation, and provide a reproducible basis for evaluating teleoperation video under realistic network constraints. Source code available at https://github.com/Dzxx623/VISTA.
Keywords
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