141,409 research outputs found
DyNetKAT: An Algebra of Dynamic Networks
We introduce a formal language for specifying dynamic updates for Software
Defined Networks. Our language builds upon Network Kleene Algebra with Tests
(NetKAT) and adds constructs for synchronisations and multi-packet behaviour to
capture the interaction between the control- and data-plane in dynamic updates.
We provide a sound and ground-complete axiomatisation of our language. We
exploit the equational theory to provide an efficient reasoning method about
safety properties for dynamic networks. We implement our equational theory in
DyNetiKAT -- a tool prototype, based on the Maude Rewriting Logic and the
NetKAT tool, and apply it to a case study. We show that we can analyse the case
study for networks with hundreds of switches using our initial tool prototype
State-of-the-art on evolution and reactivity
This report starts by, in Chapter 1, outlining aspects of querying and updating resources on
the Web and on the Semantic Web, including the development of query and update languages
to be carried out within the Rewerse project.
From this outline, it becomes clear that several existing research areas and topics are of
interest for this work in Rewerse. In the remainder of this report we further present state of
the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give
an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs;
in Chapter 4 event-condition-action rules, both in the context of active database systems and
in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks
ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra
Background: Many biological systems are modeled qualitatively with discrete
models, such as probabilistic Boolean networks, logical models, Petri nets, and
agent-based models, with the goal to gain a better understanding of the system.
The computational complexity to analyze the complete dynamics of these models
grows exponentially in the number of variables, which impedes working with
complex models. Although there exist sophisticated algorithms to determine the
dynamics of discrete models, their implementations usually require
labor-intensive formatting of the model formulation, and they are oftentimes
not accessible to users without programming skills. Efficient analysis methods
are needed that are accessible to modelers and easy to use. Method: By
converting discrete models into algebraic models, tools from computational
algebra can be used to analyze their dynamics. Specifically, we propose a
method to identify attractors of a discrete model that is equivalent to solving
a system of polynomial equations, a long-studied problem in computer algebra.
Results: A method for efficiently identifying attractors, and the web-based
tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other
analysis methods for discrete models. ADAM converts several discrete model
types automatically into polynomial dynamical systems and analyzes their
dynamics using tools from computer algebra. Based on extensive experimentation
with both discrete models arising in systems biology and randomly generated
networks, we found that the algebraic algorithms presented in this manuscript
are fast for systems with the structure maintained by most biological systems,
namely sparseness, i.e., while the number of nodes in a biological network may
be quite large, each node is affected only by a small number of other nodes,
and robustness, i.e., small number of attractors
A Logic for Non-Deterministic Parallel Abstract State Machines
We develop a logic which enables reasoning about single steps of
non-deterministic parallel Abstract State Machines (ASMs). Our logic builds
upon the unifying logic introduced by Nanchen and St\"ark for reasoning about
hierarchical (parallel) ASMs. Our main contribution to this regard is the
handling of non-determinism (both bounded and unbounded) within the logical
formalism. Moreover, we do this without sacrificing the completeness of the
logic for statements about single steps of non-deterministic parallel ASMs,
such as invariants of rules, consistency conditions for rules, or step-by-step
equivalence of rules.Comment: arXiv admin note: substantial text overlap with arXiv:1602.0748
Hybrid Information Flow Analysis for Programs with Arrays
Information flow analysis checks whether certain pieces of (confidential)
data may affect the results of computations in unwanted ways and thus leak
information. Dynamic information flow analysis adds instrumentation code to the
target software to track flows at run time and raise alarms if a flow policy is
violated; hybrid analyses combine this with preliminary static analysis.
Using a subset of C as the target language, we extend previous work on hybrid
information flow analysis that handled pointers to scalars. Our extended
formulation handles arrays, pointers to array elements, and pointer arithmetic.
Information flow through arrays of pointers is tracked precisely while arrays
of non-pointer types are summarized efficiently.
A prototype of our approach is implemented using the Frama-C program analysis
and transformation framework. Work on a full machine-checked proof of the
correctness of our approach using Isabelle/HOL is well underway; we present the
existing parts and sketch the rest of the correctness argument.Comment: In Proceedings VPT 2016, arXiv:1607.0183
Introducing Dynamic Behavior in Amalgamated Knowledge Bases
The problem of integrating knowledge from multiple and heterogeneous sources
is a fundamental issue in current information systems. In order to cope with
this problem, the concept of mediator has been introduced as a software
component providing intermediate services, linking data resources and
application programs, and making transparent the heterogeneity of the
underlying systems. In designing a mediator architecture, we believe that an
important aspect is the definition of a formal framework by which one is able
to model integration according to a declarative style. To this purpose, the use
of a logical approach seems very promising. Another important aspect is the
ability to model both static integration aspects, concerning query execution,
and dynamic ones, concerning data updates and their propagation among the
various data sources. Unfortunately, as far as we know, no formal proposals for
logically modeling mediator architectures both from a static and dynamic point
of view have already been developed. In this paper, we extend the framework for
amalgamated knowledge bases, presented by Subrahmanian, to deal with dynamic
aspects. The language we propose is based on the Active U-Datalog language, and
extends it with annotated logic and amalgamation concepts. We model the sources
of information and the mediator (also called supervisor) as Active U-Datalog
deductive databases, thus modeling queries, transactions, and active rules,
interpreted according to the PARK semantics. By using active rules, the system
can efficiently perform update propagation among different databases. The
result is a logical environment, integrating active and deductive rules, to
perform queries and update propagation in an heterogeneous mediated framework.Comment: Other Keywords: Deductive databases; Heterogeneous databases; Active
rules; Update
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