An empirical study of software reliability in SDN controllers

Vizarreta, Petra; Trivedi, Kishor S.; Helvik, Bjarne E.; Heegaard, Poul E.; Kellerer, Wolfgang; Machuca, Carmen Mas

doi:10.23919/cnsm.2017.8256002

Cited by 14 publications

(6 citation statements)

References 19 publications

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“…Weibull distributions. The temporal variations in software failure rates due to reliability growth are modelled as Non-Homogeneous Poisson Process (NHPP) in [17], [44]. Longo et al [43] discuss the limitations of Markovian models, and assume the reliability of the controller to follow phase-type distribution (generalized hypoexponential distribution), which captures better the changes in operational conditions, when some of the controller instances fail.…”

Section: B Model-based Studies On Sdn Control Plane Dependabilitymentioning

confidence: 99%

DASON: Dependability Assessment Framework for Imperfect Distributed SDN Implementations

Vizarreta

Trivedi

Mendiratta³

et al. 2020

IEEE Trans. Netw. Serv. Manage.

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In Software Defined Networking (SDN), network programmability is enabled through a logically centralized control plane. Production networks deploy multiple controllers for scalability and reliability reasons, which in turn rely on distributed consensus protocols to operate in a logically centralized manner. However, bugs in distributed control plane can have disastrous effects on the data plane, e.g., losing traffic by installing paths containing blackholes. In this paper we study the prevalence of issues in state-of-the-art distributed frameworks in SDN, by analyzing 500+ + + issues reported in two of the largest open source SDN controller platforms: Open Network Operating System (ONOS) and OpenDaylight (ODL), during the period between 2014-2019. We identify system vulnerabilities, localize dependability bottlenecks, and provide stochastic models for a holistic assessment of system dependability.

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Section: B Model-based Studies On Sdn Control Plane Dependabilitymentioning

confidence: 99%

DASON: Dependability Assessment Framework for Imperfect Distributed SDN Implementations

Vizarreta

Trivedi

Mendiratta³

et al. 2020

IEEE Trans. Netw. Serv. Manage.

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“…Our study aims to provide a framework to assess the maturity of SDN controllers, from the perspective of software developers and network operators. We extend our previous work [9], which focused on applicability of SRGM and software reliability of ONOS open source controller. In this article we extend our study to OpenDaylight controller platform, and explore different applications of our framework crucial for an efficient management of SDN-networks.…”

Section: Our Contributionmentioning

confidence: 84%

“…The performance reports and benchmarks on SDN controllers are still limited to scalability and latency related metrics, such as flow burst install throughput or flow reroute latency. The reliability of the controller software, which is still a big concern and a major obstacle for the wide spread adoption of SDN in commercial telecom and industrial networks [6], is addressed only by a limited number of studies [7]- [9].…”

Section: A Motivation and Problem Definitionmentioning

confidence: 99%

Assessing the Maturity of SDN Controllers With Software Reliability Growth Models

Vizarreta

Trivedi

Helvik

et al. 2018

IEEE Trans. Netw. Serv. Manage.

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In Software Defined Networking (SDN) critical control plane functions are offloaded to a software entity known as the SDN controller. Today's SDN controllers are complex software systems, owing to heterogeneity of networks and forwarding devices they support, and are inherently prone to bugs. Our previous work showed that Software Reliability Growth Models (SRGM) can model the stochastic nature of bug manifestation process open source SDN controllers. In this article we focus on different applications of our SRGM framework crucial for an efficient management of SDN-based networks. We provide guidelines for network operators to decide when the controller software is mature enough to be deployed in operational environment, based on the reliability requirements of network applications, and quantify the marginal benefits of the prolonged testing phase on the software quality. We show how the accuracy of software reliability prediction in the early phase of the software lifecycle can be improved by extrapolating the behaviour of previous controller software releases. We also propose software maturity metrics, that can be used by operators to discriminate between the competing SDN controller designs, i.e., ONOS and OpenDaylight, when software reliability is a major concern.

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“…It can be caused by hardware or software faults (e.g., power cut, bug); -controller: when a controller fails, the existing data flows keep working but no new flows can be set or existing flows teared down. Controller failures may be caused by hardware (e.g., hardware malfunction on the machine hosting it) or by software [49,50].…”

Section: Problem Definitionmentioning

confidence: 99%