Conference proceeding
Making Sense of Constellations: Methodologies for Understanding Starlink's Scheduling Algorithms
CoNEXT 2023: Companion of the 19th International Conference on emerging Networking EXperiments and Technologies, Vol.December 2023, pp.37-43
CoNEXT 2023: The 19th International Conference on emerging Networking EXperiments and Technologies (Paris, France, 12/05/2023–12/08/2023)
12/05/2023
DOI: 10.1145/3624354.3630586
Appears in UI Libraries Support Open Access
Abstract
Starlink constellations are currently the largest LEO WAN and have seen considerable interest from the research community. In this paper, we use high-frequency and high-fidelity measurements to uncover evidence of hierarchical traffic controllers in Starlink -- a global controller which allocates satellites to terminals and an on-satellite controller that schedules transmission of user flows. We then devise a novel approach for identifying how satellites are allocated to user terminals. Using data gathered with this approach, we measure the characteristics of the global controller and identify the factors that influence the allocation of satellites to terminals. Finally, we use this data to build a model which approximates Starlink's global scheduler. Our model is able to predict the characteristics of the satellite allocated to a terminal at a specific location and time with reasonably high accuracy and at a rate significantly higher than baseline.
Details
- Title: Subtitle
- Making Sense of Constellations: Methodologies for Understanding Starlink's Scheduling Algorithms
- Creators
- Hammas Bin TanveerMike PucholRachee SinghAntonio BianchiRishab Nithyanand
- Resource Type
- Conference proceeding
- Publication Details
- CoNEXT 2023: Companion of the 19th International Conference on emerging Networking EXperiments and Technologies, Vol.December 2023, pp.37-43
- Conference
- CoNEXT 2023: The 19th International Conference on emerging Networking EXperiments and Technologies (Paris, France, 12/05/2023–12/08/2023)
- DOI
- 10.1145/3624354.3630586
- Publisher
- Association for Computing Machinery (ACM)
- Grant note
- DOI: 10.13039/https://doi.org/10.13039/100000001, name: National Science Foundation, award: 1953983
- Language
- English
- Date published
- 12/05/2023
- Academic Unit
- Center for Social Science Innovation; Computer Science; Public Policy Center (Archive); Law Faculty
- Record Identifier
- 9984517157902771
Metrics
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