Tracer: A Tool for Race Detection in Software Defined Network Models

Autor:	Caltais, Georgiana, Zangiabady, Mahboobeh, Zvirbulis, Ervin
Rok vydání:	2024
Předmět:	Computer Science - Formal Languages and Automata Theory Computer Science - Networking and Internet Architecture Computer Science - Symbolic Computation
Zdroj:	EPTCS 410, 2024, pp. 84-98
Druh dokumentu:	Working Paper
DOI:	10.4204/EPTCS.410.6
Popis:	Software Defined Networking (SDN) has become a new paradigm in computer networking, introducing a decoupled architecture that separates the network into the data plane and the control plane. The control plane acts as the centralized brain, managing configuration updates and network management tasks, while the data plane handles traffic based on the configurations provided by the control plane. Given its asynchronous distributed nature, SDN can experience data races due to message passing between the control and data planes. This paper presents Tracer, a tool designed to automatically detect and explain the occurrence of data races in DyNetKAT SDN models. DyNetKAT is a formal framework for modeling and analyzing SDN behaviors, with robust operational semantics and a complete axiomatization implemented in Maude. Built on NetKAT, a language leveraging Kleene Algebra with Tests to express data plane forwarding behavior, DyNetKAT extends these capabilities by adding primitives for communication between the control and data planes. Tracer exploits the DyNetKAT axiomatization and enables race detection in SDNs based on Lamport vector clocks. Tracer is a publicly available tool. Comment: In Proceedings FROM 2024, arXiv:2410.23020
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2410.23763 Zobrazit plný text záznamu View this record from Arxiv