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@@ -40,7 +40,7 @@ that generate the routing tables from the control plane specifications.
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Let us consider the verification of forwarding rules in MPLS routing tables as an example.
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In a nutshell, in MPLS, packet labels can be nested
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in order to provide tunneling through the network or to handle link
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failures by fast-reroute mechanism. This mechanism relies on pushing a new MPLS
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failures by the fast-reroute mechanism. The mechanism relies on pushing a new MPLS
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label on top of the label stack, to redirect the flow
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to go around the failed link. This mechanism can be applied several times
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in case of multiple link failures, creating larger and larger (in theory: unbounded)
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header of the query can each be converted to first a
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Nondeterministic Finite Automaton (NFA) and then to a Pushdown
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Automaton (PDA). The path query is converted to an NFA, which can then be used to restrict (by synchronous product)
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the behaviour of the PDA constructed based on the network model.
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The three PDAs can be combined into a single PDA that we can give
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the behavior of the PDA constructed based on the network model.
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The three PDAs can be combined into a single PDA that can be given
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to the backend engine that checks the emptiness of the PDA language.
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In case the language is nonempty, we can return a witness trace
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to demonstrate the reason why the query is satisfied. All these operations can be performed in polynomial time,
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As a case study and to explore the feasibility of such an automata-theoretic approach,
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we developed a framework, the AalWiNes suite, which allows to load an arbitrary network topology
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(e.g., from the topology zoo dataset) as well as a set of router configurations (e.g., from Juniper routers).
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The configurations are then put into a standardized, intermediate format which is vendor independent.
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The configurations are put into a standardized, intermediate format which is vendor independent.
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The user can then define a query as described above, which leads the tool to prompt with a result
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(e.g. a trace). AalWiNes is a joint work at Aalborg University and the University of Vienna.
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@@ -108,8 +108,8 @@ We refer to our [tool website](https://aalwines.cs.aau.dk/) as well as to our
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## Conclusion and future work
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We consider providing a low runtime critical for the success of network verification,
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and reasoning about failures seems particularly challenging.
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Our aim is to provide a low runtime which is critical for the success of network
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verification, however, reasoning about failures seems particularly challenging with respect to the computational complexity.
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While not every network may allow for a polynomial-time analysis,
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we see much potential in automata-theoretic approaches,
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and we hope this article can inspire the community to conduct more research
@@ -119,7 +119,7 @@ We understand our approach as a first step and believe that it opens the door to
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verify many other infinite state systems whose configurations
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cannot explicitly be represented anymore.
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For example, we have recently extended AalWiNes to support a witness trace generation which
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accounts for additional metrics, and for example selects (among a possibly infinite number of witness traces)
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accounts for additional metrics; for example, the tool can now select (among a possibly infinite number of witness traces)
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the ones that minimize the number of hops, latency, or the stack height that corresponds to the number
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of MPLS tunnels. This is
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achieved by extending the PDA reachability analysis with multi-dimensional weights.

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