Name Space Analysis: Verification of Named Data Network Data Planes

Abstract

Named Data Networking (NDN) has many forwarding behaviors, strategies, and protocols to enable the benefits of Information-Centric Networking. This additional functionality introduces complexity, motivating the need for a tool to help reason about and verify that basic properties of an NDN data plane are guaranteed. This paper proposes Name Space Analysis (NSA), a network verification framework to model and analyze NDN data planes. NSA can take as input one or more snapshots, each representing a state of the data plane. It then provides the verification result against specified properties. NSA builds on the theory of Header Space Analysis, and extends it in a number of ways, e.g., supporting variable-sized headers with flexible formats, introduction of name space functions, allowing for name-based properties such as content reachability and name leakage-freedom, and multi-snapshot verification such as equivalence checks. These important additions reflect the behavior and requirements of NDN, requiring modeling and verification foundations fundamentally different from those of traditional host-centric networks. As a case study, we show how NSA can detect name space conflicts in NDN, which can be often hard to catch. Leveraging the learning from this study, we outline a conflict detection and resolution protocol and a name space registry to avoid such conflicts. We have implemented NSA and identified a number of optimizations to enhance the efficiency of verification. Results from our evaluations, using snapshots from various synthetic test cases and the real-world NDN testbed, show how NSA is effective, in finding errors, has good performance, and is scalable.