Towards Efficient and Scalable Internet Cross-Layer Mapping

Understanding the topology of the global Internet is crucial for advancements in network performance, resilience, and policy-making. Most existing mapping frameworks, focusing separately on logical or physical connectivity, provide fragmented insights and fail to capture the full complexity of the Internet's structure. This paper proposes an efficient cross-layer mapping framework that integrates both logical and physical layer perspectives, addressing the significant limitations of current cross-layer mapping frameworks such as iGDB and Nautilus. By leveraging several data sources across layers and designing adaptive and scalable algorithms for mapping, we aim to improve mapping accuracy. Our framework has potential applications in enhancing network performance, resilience, policy-making, and national security.