Fast Control Plane Analysis Using an Abstract Representation

Gember-Jacobson, Aaron; Viswanathan, Raajay; Akella, Aditya; Mahajan, Ratul

doi:10.1145/2934872.2934876

Cited by 114 publications

(66 citation statements)

References 16 publications

(21 reference statements)

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“…Data Plane Logical Rules (R logical ) [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42] (P == R logical ) (P == P logical ) [5,[21][22][23][24][25] (P == P physical ) [20] (P logical == P physical ) control, and data plane -with their components. The management plane establishes the network-wide policy P, which corresponds to the network operator's intent.…”

Section: Control Planementioning

confidence: 99%

Toward Consistent SDNs: A Case for Network State Fuzzing

Shukla

Saidi

Schmid

et al. 2020

IEEE Trans. Netw. Serv. Manage.

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The conventional wisdom is that a software-defined network (SDN) operates under the premise that the logically centralized control plane has an accurate representation of the actual data plane state. Nevertheless, bugs, misconfigurations, faults or attacks can introduce inconsistencies that undermine correct operation. Previous work in this area, however, lacks a holistic methodology to tackle this problem and thus, addresses only certain parts of the problem. Yet, the consistency of the overall system is only as good as its least consistent part.Motivated by an analogy of network consistency checking with program testing, we propose to add active probe-based network state fuzzing to our consistency check repertoire. Hereby, our system, PAZZ, combines production traffic with active probes to continuously test if the actual forwarding path and decision elements (on the data plane) correspond to the expected ones (on the control plane). Our insight is that active traffic covers the inconsistency cases beyond the ones identified by passive traffic. PAZZ prototype was built and evaluated on topologies of varying scale and complexity. Our results show that PAZZ requires minimal network resources to detect persistent data plane faults through fuzzing and localize them quickly.

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Section: Control Planementioning

confidence: 99%

Toward Consistent SDNs: A Case for Network State Fuzzing

Shukla

Saidi

Schmid

et al. 2020

IEEE Trans. Netw. Serv. Manage.

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“…In addition to the formal tools and techniques reviewed in Section , there is another set of tools which are used in general network verification . These tools can also be used to verify SDN infrastructure.…”

Section: Some Other Relevant Workmentioning

confidence: 99%

“…These tools can also be used to verify SDN infrastructure. These tool can be employed in verifying the correctness of data‐plane, middleboxes, and control‐plane . Further, we have also studied some additional verification tools for their applications in different domains of SDN enable networks.…”

Section: Some Other Relevant Workmentioning

confidence: 99%

“…This VMN model then uses Veriflow and SMT solver for model checking and property verification. A VMN model is developed based on the middlebox manual or a document having high‐level description of the middlebox. ARC: This work tends to model and verify control plane using an abstract representation for control‐plane (ARC) . An ARC is a graph depicting all possible paths of a network.…”

Section: Some Other Relevant Workmentioning

confidence: 99%

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Formal modeling and verification of software‐defined networks: A survey

2019

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Summary Unlike traditional networking devices, control and management plane are decoupled from data plane in software‐defined networks (SDN). The logically centralized control and management plane facilitate dynamic orchestration of network resources, services, and policies by writing software programs. This provides much needed flexibility and programmability where networking rules and policies can be modified dynamically depending upon the application context. As the operation of network services entirely depends on a program, a small fault may induce several issues which can adversely affect the expected behavior of the network. Formal modeling and verification help in catching inconsistencies and existence of errors prior to the deployment of the programs that control the behavior of a network. In this paper, we provide a comprehensive survey of tools and techniques available in the literature for formal modeling and verification of SDN. These tools and techniques are classified based on their types, the components of SDN where they can be applied, and the design and development phase when they are utilized. In particular, their respective benefits and limitations are discussed in terms of ease of use, interfaces, and the ability to capture and verify intended network properties.

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“…Some focus on the control plane, while others, in the data plane. Approaches that target the control plane proactively analyze their network operations, being useful to verify that the control plane does not yield configurations that violate the desired properties (LIU et al, 2017;BECK-ETT et al, 2017;GEMBER-JACOBSON et al, 2016;FOGEL et al, 2015;CANINI et al, 2012b).…”

Section: Related Workmentioning

confidence: 99%