65 research outputs found
A fixed point theorem for Boolean networks expressed in terms of forbidden subnetworks
We are interested in fixed points in Boolean networks, functions from to itself. We define the subnetworks of as the restrictions of to the hypercubes contained in , and we exhibit a class of Boolean networks, called even or odd self-dual networks, satisfying the following property: if a network has no subnetwork in , then it has a unique fixed point. We then discuss this "forbidden subnetworks theorem''. We show that it generalizes the following fixed point theorem of Shih and Dong: if, for every in , there is no directed cycle in the directed graph whose the adjacency matrix is the discrete Jacobian matrix of evaluated at point , then has a unique fixed point. We also show that contains the class of networks whose the interaction graph is a directed cycle, but that the absence of subnetwork in does not imply the existence and the uniqueness of a fixed point
Fixed point theorems for Boolean networks expressed in terms of forbidden subnetworks
We are interested in fixed points in Boolean networks, {\em i.e.} functions
from to itself. We define the subnetworks of as the
restrictions of to the subcubes of , and we characterizes a
class of Boolean networks satisfying the following property:
Every subnetwork of has a unique fixed point if and only if has no
subnetwork in . This characterization generalizes the fixed point
theorem of Shih and Dong, which asserts that if for every in
there is no directed cycle in the directed graph whose the adjacency matrix is
the discrete Jacobian matrix of evaluated at point , then has a
unique fixed point. Then, denoting by (resp. )
the networks whose the interaction graph is a positive (resp. negative) cycle,
we show that the non-expansive networks of are exactly the
networks of ; and for the class of
non-expansive networks we get a "dichotomization" of the previous forbidden
subnetwork theorem: Every subnetwork of has at most (resp. at least) one
fixed point if and only if has no subnetworks in (resp.
) subnetwork. Finally, we prove that if is a conjunctive
network then every subnetwork of has at most one fixed point if and only if
has no subnetwork in .Comment: 40 page
Proceedings of AUTOMATA 2011 : 17th International Workshop on Cellular Automata and Discrete Complex Systems
International audienceThe proceedings contain full (reviewed) papers and short (non reviewed) papers that were presented at the workshop
A theory of flow network typings and its optimization problems
Many large-scale and safety critical systems can be modeled as flow networks. Traditional approaches for the analysis of flow networks are whole-system approaches in that they require prior knowledge of the entire network before an analysis is undertaken, which can quickly become intractable as the size of network increases.
In this thesis we study an alternative approach to the analysis of flow networks, which is modular, incremental and order-oblivious. The formal mechanism for realizing this compositional approach is an appropriately defined theory of network typings. Typings are formalized differently depending on how networks are specified and which of their properties is being verified. We illustrate this approach by considering a particular family of flow networks, called additive flow networks.
In additive flow networks, every edge is assigned a constant gain/loss factor which is activated provided a non-zero amount of flow enters that edge. We show that the analysis of additive flow networks, more specifically the max-flow problem, is NP-hard, even when the underlying graph is planar.
The theory of network typings gives rise to different forms of graph decomposition problems. We focus on one problem, which we call the graph reassembling problem. Given an abstraction of a flow network as a graph G = (V,E), one possible definition of this problem is specified in two steps: (1) We cut every edge of G into two halves to obtain a collection of |V| one-vertex components, and (2) we splice the two halves of all the edges, one edge at a time, in some order that minimizes the complexity of constructing a typing for G, starting from the typings of its one-vertex components.
One optimization is minimizing “maximum” edge-boundary degree of components encountered during the reassembling of G (denoted as α measure). Another is to minimize the “sum” of all edge-boundary degrees encountered during this process (denoted by β measure). Finally, we study different variations of graph reassembling (with respect to minimizing α or β) and their relation with problems such as Linear Arrangement, Routing Tree Embedding, and Tree Layout
Network Security Automation
L'abstract è presente nell'allegato / the abstract is in the attachmen
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