Abstract
ProbNV is a new framework for probabilistic network control plane verification that strikes a balance between generality and scalability. ProbNV is general enough to encode a wide range of features from the most common protocols (eBGP and OSPF) and yet scalable enough to handle challenging properties, such as probabilistic all-failures analysis of medium-sized networks with 100-200 devices. When there are a small, bounded number of failures, networks with up to 500 devices may be verified in seconds. ProbNV operates by translating raw CISCO configurations into a probabilistic and functional programming language designed for network verification. This language comes equipped with a novel type system that characterizes the sort of representation to be used for each data structure: concrete for the usual representation of values; symbolic for a BDD-based representation of sets of values; and multi-value for an MTBDD-based representation of values that depend upon symbolics. Careful use of these varying representations speeds execution of symbolic simulation of network models. The MTBDD-based representations are also used to calculate probabilistic properties of network models once symbolic simulation is complete. We implement the language and evaluate its performance on benchmarks constructed from real network topologies and synthesized routing policies.
Highlights
Computer networks come in all shapes and sizes, from single-router home networks to modest-sized office or university networks to the large industrial data center or wide area networks of a select few tech companies
We introduce ProbNV, a probabilistic control plane analysis system that strikes a balance between these two extremes
We find that ProbNV enables fast probabilistic verification for mid-sized networks when considering any number of node failures, and fast verification of bounded link failure scenarios even for networks with thousands of links
Summary
Computer networks come in all shapes and sizes, from single-router home networks to modest-sized office or university networks to the large industrial data center or wide area networks of a select few tech companies. Once a network grows beyond a few devices, it becomes difficult to manage and maintain as configurations for each device often involve hundreds or thousands of lines of domain-specific, assembly-like code that controls the routing process. Changes to such configurations can cause trickle-down effects and bring down services or even cut off portions of the internet [Godfrey 2016; Graham-Cumming 2020; McCarthy 2019; Sharwood 2016; Sverdlik 2012]. Many such problems are difficult to anticipate because doing so depends.
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