Vivisecting Starlink Throughput: Measurement and Prediction

Internet connectivity using low earth orbit (LEO) satellites is gaining significant traction, with nearly 3 million users worldwide. While these networks promise to provide universal broadband connectivity, they suffer from large throughput fluctuations over short time scales. We conduct an extensive evaluation of Starlink's throughput across three devices in different countries, with measurement durations ranging from one to six months. We identify various factors that cause throughput variations at varying timescales. Given our analysis, we design StarNet, a new learning-based throughput prediction system. StarNet incorporates satellite network-specific insights and accurately predicts future throughput for end users. We demonstrate that StarNet's accurate predictions can improve the experience of end user applications like video streaming.

Authors

Institutions

Publication Details

Journal
Proceedings of the ACM on Networking
Published
2025-11-24
DOI
https://doi.org/10.1145/3768971
Primary Topic
Satellite Communication Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Vivisecting Starlink Throughput: Measurement and Prediction

Deepak Vasisht, Zikun Liu, Sarah Tanveer, Fan-Xue Gabriella Reidys
Proceedings of the ACM on Networking
Satellite Communication Systems
article

Vivisecting Starlink Throughput: Measurement and Prediction

Deepak Vasisht, Zikun Liu, Sarah Tanveer, Fan-Xue Gabriella Reidys
article en

Abstract

Internet connectivity using low earth orbit (LEO) satellites is gaining significant traction, with nearly 3 million users worldwide. While these networks promise to provide universal broadband connectivity, they suffer from large throughput fluctuations over short time scales. We conduct an extensive evaluation of Starlink's throughput across three devices in different countries, with measurement durations ranging from one to six months. We identify various factors that cause throughput variations at varying timescales. Given our analysis, we design StarNet, a new learning-based throughput prediction system. StarNet incorporates satellite network-specific insights and accurately predicts future throughput for end users. We demonstrate that StarNet's accurate predictions can improve the experience of end user applications like video streaming.

Proceedings of the ACM on NetworkingVol. 3(CoNEXT4)
University of Wisconsin–Madison (US), University of Illinois Urbana-Champaign (US)
Openalex Percentile: Top 53%
Satellite Communication Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Vivisecting Starlink Throughput: Measurement and Prediction — Deepak Vasisht, Zikun Liu, et al. · Proceedings of the ACM on Networking (2025) | TGRS Research Map | TGRS