The networking industry is currently undergoing a steady trend of softwarization. Yet, network engineers suffer from the lack of software development tools that support programming of new protocols. We are creating a cost analysis tool for the P4 programming language, that automatically verifies whether the developed program meets soft deadline requirements imposed by the network. In this paper, we present an approach to estimate the average execution time of P4 program based on control flow graphs. Our approach takes into consideration that many of the parts of P4 are implementation-defined: required information can be added in through incremental refinement, while missing information is handled by falling back to less precise defaults. We illustrate application of this approach to a P4 protocol in two case studies: we use it to examine the effect of a compiler optimization in the deparse stage, and to show how it enables cost modelling complex lookup table implementations. Finally, we assess future research tasks to be completed before the tool is ready for real-world usage.

The networking dataplane is going through a paradigm shift as softwarization of switches sees an increased pull from the market. Yet, software tooling to support development with these new technologies is still in its infancy.In this work, we introduce a framework for verifying performance requirement conformance of data plane protocols defined in the P4 language . We present a framework that transforms a P4 program in a versatile symbolic formula which can be utilized to answer various performance queries. We represented the system using denotational semantics and it can be easily extended with low-level target-dependent information. We demonstrate the operation of this system on a toy specification.

Next-generation networks focus on scale and scope at the price of increasing complexity, leading to difficulties in network design and planning. As a result, anticipating all hardware- and software-related factors of network performance requires time-consuming and expensive benchmarking. This work presents a framework and software tool for automatically inferring the performance of P4 programmable network switches based on the P4 source code and probabilistic models of the execution environment with the hope of eliminating the requirement of the costly set-up of networked hardware and conducting benchmarks. We designed the framework using a top-down approach. First, we transform high-level P4 programs into a representation that can be refined incrementally by adding probabilistic environment models of increasing levels of complexity in order to improve the estimation precision. Then, we use the PRISM probabilistic model checker to perform the heavy weight calculations involved in static performance prediction. We present a formalization of the performance estimation problem, detail our solution, and illustrate its usage and validation through a case study conducted using a small P4 program and the P4C-BM reference switch. We show that the framework is already capable of performing estimation, and it can be extended with more concrete information to yield better estimates.

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