Understanding Cross-Cloud Interconnects: Hands-On Measurements and Cost Optimization
For cloud users needing cost-effective cross-cloud data transfers, this work provides the first empirical characterization of CCI and a provably optimal dynamic algorithm to handle provisioning delays and demand uncertainty.
This paper presents the first comprehensive study of Cross-Cloud Interconnect (CCI) services, including empirical measurements across AWS-GCP, and introduces ToggleCCI, a dynamic cost-optimization algorithm that adapts between VPN and CCI. Using real-world traffic traces, ToggleCCI consistently tracks the best static policy and delivers substantial cost savings.
New services such as Google Cross-Cloud Interconnect (CCI) address the rise in fast and large-scale cross-cloud data transfers. CCI offers dedicated high-throughput links with low per-GB transfer costs, but also involves high fixed leasing fees and multi-day provisioning delays. This combination makes cost optimization difficult because traffic patterns are unpredictable. This paper presents the first comprehensive study of CCI-like services. We begin with an empirical characterization of CCI and its alternatives using direct measurements across AWS-GCP interconnects. We then introduce ToggleCCI, a new dynamic cost-optimization algorithm designed to handle provisioning delays and uncertainty in future demand. ToggleCCI adapts by switching between VPN and CCI based on cost trends observed over a sliding time window. We prove that ToggleCCI achieves asymptotic optimality under sustained high-demand or low-demand regimes. Finally, using real-world traffic traces, we show that ToggleCCI consistently tracks the best static policy for each scenario and delivers substantial cost savings.