🤖 AI Summary
This work addresses the challenge of accurately assessing the resilience of end-to-end applications in real-world communication networks due to limited transparency from network operators. To overcome this, the authors propose DRACO, a novel framework that enables systematic modeling and quantitative evaluation of application deployments across national-scale networks without relying on proprietary operator data. DRACO integrates network modeling, publicly available datasets, synthetic data generation, and resilience metric computation to construct a scalable end-to-end evaluation pipeline. The framework was successfully applied to nationwide networks in Germany and France, demonstrating its effectiveness in handling heterogeneous data sources and enabling large-scale resilience assessments.
📝 Abstract
Billions of users take Internet connectivity for granted and use it daily to access applications deployed anywhere around the globe. What users perceive as a seamless connection between their end device and the application server involves a complex system of systems operated by various actors. Failures in any of these systems disrupt user-to-application connectivity if the communication network is not resilient. Since communication networks are a critical infrastructure as part of ICT, real-world operators rarely disclose information about them. This makes it difficult to measure the end-to-end resilience of deployments, because it requires guessing topologies and the availability of the involved systems.
This paper presents DRACO, a framework for modeling communication networks and measuring end-to-end resilience of application deployments. It enables configuring application deployments across arbitrary communication networks and evaluating their availability, robustness, and resilience. We demonstrate the functional scope of DRACO by modeling nationwide application deployments in Germany and France, highlighting its compatibility with a wide variety of public data sources and synthetic data.