10,105 research outputs found
A Projection Argument for Differential Inclusions, with Applications to Persistence of Mass-Action Kinetics
Motivated by questions in mass-action kinetics, we introduce the notion of
vertexical family of differential inclusions. Defined on open hypercubes, these
families are characterized by particular good behavior under projection maps.
The motivating examples are certain families of reaction networks -- including
reversible, weakly reversible, endotactic, and strongly endotactic reaction
networks -- that give rise to vertexical families of mass-action differential
inclusions. We prove that vertexical families are amenable to structural
induction. Consequently, a trajectory of a vertexical family approaches the
boundary if and only if either the trajectory approaches a vertex of the
hypercube, or a trajectory in a lower-dimensional member of the family
approaches the boundary. With this technology, we make progress on the global
attractor conjecture, a central open problem concerning mass-action kinetics
systems. Additionally, we phrase mass-action kinetics as a functor on reaction
networks with variable rates.Comment: v5: published version; v3 and v4: minor additional edits; v2:
contains more general version of main theorem on vertexical families,
including its accompanying corollaries -- some of them new; final section
contains new results relating to prior and future research on persistence of
mass-action systems; improved exposition throughou
Edge-Fault Tolerance of Hypercube-like Networks
This paper considers a kind of generalized measure of fault
tolerance in a hypercube-like graph which contain several well-known
interconnection networks such as hypercubes, varietal hypercubes, twisted
cubes, crossed cubes and M\"obius cubes, and proves for any with by the induction on
and a new technique. This result shows that at least edges of
have to be removed to get a disconnected graph that contains no vertices of
degree less than . Compared with previous results, this result enhances
fault-tolerant ability of the above-mentioned networks theoretically
A general analytical model of adaptive wormhole routing in k-ary n-cubes
Several analytical models of fully adaptive routing have recently been proposed for k-ary n-cubes and hypercube networks under the uniform traffic pattern. Although,hypercube is a special case of k-ary n-cubes topology, the modeling approach for hypercube is more accurate than karyn-cubes due to its simpler structure. This paper proposes a general analytical model to predict message latency in wormhole-routed k-ary n-cubes with fully adaptive routing that uses a similar modeling approach to hypercube. The analysis focuses Duato's fully adaptive routing algorithm [12], which is widely accepted as the most general algorithm for achieving adaptivity in wormhole-routed networks while allowing for an efficient router implementation. The proposed model is general enough that it can be used for hypercube and other fully adaptive routing algorithms
Canalization and Symmetry in Boolean Models for Genetic Regulatory Networks
Canalization of genetic regulatory networks has been argued to be favored by
evolutionary processes due to the stability that it can confer to phenotype
expression. We explore whether a significant amount of canalization and partial
canalization can arise in purely random networks in the absence of evolutionary
pressures. We use a mapping of the Boolean functions in the Kauffman N-K model
for genetic regulatory networks onto a k-dimensional Ising hypercube to show
that the functions can be divided into different classes strictly due to
geometrical constraints. The classes can be counted and their properties
determined using results from group theory and isomer chemistry. We demonstrate
that partially canalized functions completely dominate all possible Boolean
functions, particularly for higher k. This indicates that partial canalization
is extremely common, even in randomly chosen networks, and has implications for
how much information can be obtained in experiments on native state genetic
regulatory networks.Comment: 14 pages, 4 figures; version to appear in J. Phys.
Optimal Networks from Error Correcting Codes
To address growth challenges facing large Data Centers and supercomputing
clusters a new construction is presented for scalable, high throughput, low
latency networks. The resulting networks require 1.5-5 times fewer switches,
2-6 times fewer cables, have 1.2-2 times lower latency and correspondingly
lower congestion and packet losses than the best present or proposed networks
providing the same number of ports at the same total bisection. These advantage
ratios increase with network size. The key new ingredient is the exact
equivalence discovered between the problem of maximizing network bisection for
large classes of practically interesting Cayley graphs and the problem of
maximizing codeword distance for linear error correcting codes. Resulting
translation recipe converts existent optimal error correcting codes into
optimal throughput networks.Comment: 14 pages, accepted at ANCS 2013 conferenc
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