# Skyplane: Optimizing Transfer Cost and Throughput Using Cloud-Aware Overlays

arXiv: https://arxiv.org/abs/2210.07259 · HTML: https://mlsanity.com/paper/2210.07259/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Oct 2022.

## Built on by (most cited first, 5 of 5)

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- [Improving training time and GPU utilization in geo-distributed language model training](https://mlsanity.com/paper/2411.14458/) (2024)
- [ShadowServe: Interference-Free KV Cache Fetching for Distributed Prefix Caching](https://mlsanity.com/paper/2509.16857/) (2025)
- [Deployability-Centric Infrastructure-as-Code Generation: Fail, Learn, Refine, and Succeed through LLM-Empowered DevOps Simulation](https://mlsanity.com/paper/2506.05623/) (2025)
- [Empowering Computing and Networks Convergence System with Distributed Cooperative Routing](https://mlsanity.com/paper/2402.02381/) (2024)

## Abstract (arXiv)

Cloud applications are increasingly distributing data across multiple regions and cloud providers. Unfortunately, wide-area bulk data transfers are often slow, bottlenecking applications. We demonstrate that it is possible to significantly improve inter-region cloud bulk transfer throughput by adapting network overlays to the cloud setting -- that is, by routing data through indirect paths at the application layer. However, directly applying network overlays in this setting can result in unacceptable increases in cloud egress prices. We present Skyplane, a system for bulk data transfer between cloud object stores that uses cloud-aware network overlays to optimally navigate the trade-off between price and performance. Skyplane's planner uses mixed-integer linear programming to determine the optimal overlay path and resource allocation for data transfer, subject to user-provided constraints on price or performance. Skyplane outperforms public cloud transfer services by up to 4.6× for transfers within one cloud and by up to 5.0× across clouds.