Kuai: A model checker for software-defined networks

Majumdar, Rupak; Tetali, Sai Deep; Wang, Zilong

doi:10.1109/fmcad.2014.6987609

Cited by 41 publications

(63 citation statements)

References 13 publications

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“…A simplified model is used for the OpenFlow switch in order to reduce the number of states that need to be explored. The Kuai [19] checker similarly uses a simplified version of an OpenFlow switch as well as a custom controller language, but then applies partial order reduction techniques to reduce the number of states the model checker has to explore. Although performance is significantly improved, it still suffers from the state-space explosion problem associated with full model checking.…”

Section: Related Workmentioning

confidence: 99%

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SDNRacer

Miserez

Bielik

El-Hassany

et al. 2015

Proceedings of the 1st ACM SIGCOMM Symposium on Software Defined Networking Research

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Software-Defined Networking (SDN) control software executes in highly asynchronous environments where unexpected concurrency errors can lead to performance or, worse, reachability errors. Unfortunately, detecting such errors is notoriously challenging, and SDN is no exception.Fundamentally, two ingredients are needed to build a concurrency analyzer: (i) a model of how different events are ordered, and (ii) the memory locations on which event accesses can interfere. In this paper we formulate the first happens-before (HB) model for SDNs enabling one to reason about ordering between events. We also present a commutativity specification of the network switch, allowing us to elegantly capture interference between concurrent events.Based on the above, we present the first dynamic concurrency analyzer for SDNs, called SDNRACER. SDNRACER uses the HB model and the commutativity rules to identify concurrency violations. Preliminary results indicate that the detector is practically effective-it can detect harmful violations quickly.

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Section: Related Workmentioning

confidence: 99%

“…A different approach to the verification problem is taken by tools such as NICE [18], Kuai [19] and Vericon [20]. NICE [18] uses concolic execution of Python controller programs with symbolic packets and then runs a model checker to determine invariant violations.…”

Section: Related Workmentioning

confidence: 99%

SDNRacer

Miserez

Bielik

El-Hassany

et al. 2015

Proceedings of the 1st ACM SIGCOMM Symposium on Software Defined Networking Research

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“…Model checking has been used for network verification [2,18,20,26,27]. The closest to our work is the incremental checker NetPlumber [19].…”

Section: Related Workmentioning

confidence: 99%

Efficient synthesis of network updates

McClurg

Hojjat

Černý

et al. 2015

Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation

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Software-defined networking (SDN) is revolutionizing the networking industry, but current SDN programming platforms do not provide automated mechanisms for updating global configurations on the fly. Implementing updates by hand is challenging for SDN programmers because networks are distributed systems with hundreds or thousands of interacting nodes. Even if initial and final configurations are correct, naïvely updating individual nodes can lead to incorrect transient behaviors, including loops, black holes, and access control violations. This paper presents an approach for automatically synthesizing updates that are guaranteed to preserve specified properties. We formalize network updates as a distributed programming problem and develop a synthesis algorithm based on counterexample-guided search and incremental model checking. We describe a prototype implementation, and present results from experiments on real-world topologies and properties demonstrating that our tool scales to updates involving over one-thousand nodes.

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“…This reduces the state space but it also limits the invariants that can be checked to just perpacket safety properties. Kuai [37] introduces a set of partial order reduction techniques to reduce the state space. VeriCon [38] extends verification of SDN programs to check their correctness on all admissible topologies and for all possible sequences of network events.…”

Section: Related Workmentioning

confidence: 99%

Systematically testing OpenFlow controller applications

et al. 2015

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The emergence of OpenFlow-capable switches enables exciting new network functionality, at the risk of programming errors that make communication less reliable. The centralized programming model, where a single controller program manages the network, seems to reduce the likelihood of bugs. However, the system is inherently distributed and asynchronous, with events happening at different switches and end hosts, and inevitable delays affecting communication with the controller. In this paper, we present efficient, systematic techniques for testing unmodified controller programs. Our NICE tool applies model checking to explore the state space of the entire system-the controller, the switches, and the hosts. Scalability is the main challenge, given the diversity of data packets, the large system state, and the many possible event orderings. To address this, we propose a novel way to augment model checking with symbolic execution of event handlers (to identify representative packets that exercise code paths on the controller). We also present a simplified OpenFlow switch model (to reduce the state space), and effective strategies for generating event interleavings likely to uncover bugs. Our prototype tests Python applications on the popular NOX platform. In testing three real applications-a MAC-learning switch, in-network server load balancing, and energy-efficient traffic engineering-we uncover thirteen bugs.

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Kuai: A model checker for software-defined networks

Cited by 41 publications

References 13 publications

SDNRacer

SDNRacer

Efficient synthesis of network updates

Systematically testing OpenFlow controller applications

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