A General Approach to Network Configuration Verification

Beckett, Ryan; Gupta, Aarti; Mahajan, Ratul; Walker, David

doi:10.1145/3098822.3098834

Cited by 177 publications

(147 citation statements)

References 19 publications

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“…[69]- [71]), programming languages (e.g. [72]- [76]), safe network updates (e.g., [77]- [80]), data plane checking (e.g., [10], [11], [16], [25]), real-time checkers [12], [14], [30], [81], and more general network analyses (e.g., [6], [8], [9], [19], [82], [83]) together with suitable levels of abstractions (e.g., [84], [85]).…”

Section: E Discussion: Importance Of Empty Pecsmentioning

confidence: 99%

A Precise and Expressive Lattice-theoretical Framework for Efficient Network Verification

Horn

Kheradmand

Prasad

2019

2019 IEEE 27th International Conference on Network Protocols (ICNP)

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Network verification promises to detect errors, such as black holes and forwarding loops, by logically analyzing the control or data plane. To do so efficiently, the state-of-the-art (e.g., Veriflow) partitions packet headers with identical forwarding behavior into the same packet equivalence class (PEC).Recently, Yang and Lam showed how to construct the minimal set of PECs, called atomic predicates. Their construction uses Binary Decision Diagrams (BDDs). However, BDDs have been shown to incur significant overhead per packet header bit, performing poorly when analyzing large-scale data centers. The overhead of atomic predicates prompted ddNF to devise a specialized data structure of Ternary Bit Vectors (TBV) instead.However, TBVs are strictly less expressive than BDDs. Moreover, unlike atomic predicates, ddNF's set of PECs is not minimal. We show that ddNF's non-minimality is due to empty PECs. In addition, empty PECs are shown to trigger wrong analysis results. This reveals an inherent tension between precision, expressiveness and performance in formal network verification.Our paper resolves this tension through a new latticetheoretical PEC-construction algorithm, #PEC, that advances the field as follows: (i) #PEC can encode more kinds of forwarding rules (e.g., ip-tables) than ddNF and Veriflow, (ii) #PEC verifies a wider class of errors (e.g., shadowed rules) than ddNF, and (iii) on a broad range of real-world datasets, #PEC is 10× faster than atomic predicates. By achieving precision, expressiveness and performance, this paper answers a longstanding quest that has spanned three generations of formal network analysis techniques.

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Section: E Discussion: Importance Of Empty Pecsmentioning

confidence: 99%

A Precise and Expressive Lattice-theoretical Framework for Efficient Network Verification

Horn

Kheradmand

Prasad

2019

2019 IEEE 27th International Conference on Network Protocols (ICNP)

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“…Applied to the target network, the intents allow a set of possible forwarding behavior in the form of a set of forwarding paths in the network. 1 A collector then collects a subset of these paths by data plane or Figure 2: An abstract view of intent inference process control plane configuration analysis [3,12,13,19], observing the actual network traffic, etc. The collection mechanism is orthogonal to our work but we emphasize that the collector may not be able to observe all possible paths.…”

Section: Measures Of Qualitymentioning

confidence: 99%

Automatic Inference of High-Level Network Intents by Mining Forwarding Patterns

Kheradmand

2020

Proceedings of the Symposium on SDN Research

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There is a semantic gap between the high-level intents of network operators and the low-level configurations that achieve the intents. Previous works tried to bridge the gap using verification or synthesis techniques, both requiring formal specifications of the intended behavior which are rarely available or even known in the real world. This paper discusses an alternative approach for bridging the gap, namely to infer the high-level intents from the low-level network behavior. Specifically, we provide Anime, a framework and a tool that given a set of observed forwarding behavior, automatically infers a set of possible intents that best describe all observations. Our results show that Anime can infer high-quality intents from the low-level forwarding behavior with acceptable performance.

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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 tool can verify properties like reachability, loop detection, and network invariants using Z3 SMT solver Minesweeper: Minesweeper is a tool used to symbolically model the data‐plane and control‐plane and verify its correctness for a large set of properties. It uses Batfish tools to parse input for system configurations for network devices from different vendors.…”

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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A General Approach to Network Configuration Verification

Cited by 177 publications

References 19 publications

A Precise and Expressive Lattice-theoretical Framework for Efficient Network Verification

A Precise and Expressive Lattice-theoretical Framework for Efficient Network Verification

Automatic Inference of High-Level Network Intents by Mining Forwarding Patterns

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

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