# Skyplane: Optimizing transfer cost and throughput using cloud-aware overlays

### Meta Info

Presented in [NSDI 2023](https://www.usenix.org/conference/nsdi23/presentation/jain).

Authors: Paras Jain, Sam Kumar, Sarah Wooders, Shishir G Patil, Joseph E Gonzalez, Ion Stoica, *University of California, Berkeley*

Homepage: <https://skyplane.org/>

Code: <https://github.com/skyplane-project/skyplane>

## Understanding the paper

### TL;DRs

This paper presents **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*.

Its 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*.

### Comparison to Existing Work

* Consider price and elasticity (opposed to *Resilient overlay networks (RON), SOSP 2001*).
* Richer problem and solution space.

### Implementation

* Implemented in Python 3.
* Use the Gurobi library to solve MILP instances.
* Support three major cloud providers: Amazon Web Services, Microsoft Azure, and Google Cloud Platform.


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