Self-Stabilizing Master-Slave Token Circulation and Efficient Topology Computation in a Tree of Arbitrary Size

2011 ◽  
Author(s):  
Wayne Goddard ◽  
Pradip K. Srimani
Keyword(s):  
Arbitrary Size ◽  
Token Circulation ◽  
Topology Computation

SELF-STABILIZING MASTER–SLAVE TOKEN CIRCULATION AND EFFICIENT SIZE-COMPUTATION IN A UNIDIRECTIONAL RING OF ARBITRARY SIZE

2012 ◽  
Vol 23 (04) ◽  
pp. 763-777 ◽  
Author(s):  
WAYNE GODDARD ◽  
PRADIP K. SRIMANI
Keyword(s):  
Distributed Algorithms ◽  
Master Node ◽  
Arbitrary Size ◽  
Token Circulation

Self-stabilizing algorithms represent an extension of distributed algorithms in which nodes of the network have neither coordination, synchronization, nor initialization. We consider the model where there is one designated master node and all other nodes are anonymous and have constant space. Recently, Lee et al. obtained such an algorithm for determining the size of a unidirectional ring. We provide a new algorithm that converges much quicker. This algorithm exploits a token-circulation idea due to Afek and Brown. Disregarding the time for stabilization, our algorithm computes the size of the ring at the master node in O(n log n) time compared to O(n3) steps used in the algorithm by Lee et al. We have also shown that the master node, after determining the size of the ring, can compute the average of observations made at each node in O(n) rounds or O(n2) steps. It seems likely that one should be able to obtain master–slave algorithms for other problems in networks.

Self-stabilizing depth-first token circulation in arbitrary rooted networks

2000 ◽  
Vol 13 (4) ◽  
pp. 207-218 ◽  
Author(s):  
Ajoy K. Datta ◽  
Colette Johnen ◽  
Franck Petit ◽  
Vincent Villain
Keyword(s):  
Token Circulation

scholarly journals Entanglement Polytopes: Multiparticle Entanglement from Single-Particle Information

Science ◽  
2013 ◽  
Vol 340 (6137) ◽  
pp. 1205-1208 ◽  
Author(s):  
Michael Walter ◽  
Brent Doran ◽  
David Gross ◽  
Matthias Christandl
Keyword(s):  
Quantum Computing ◽  
Single Particle ◽  
Local Information ◽  
Geometric Object ◽  
Quantum States ◽  
Many Body ◽  
Arbitrary Size ◽  
Global Entanglement ◽  
Low Levels ◽  
Essential Resource

Entangled many-body states are an essential resource for quantum computing and interferometry. Determining the type of entanglement present in a system usually requires access to an exponential number of parameters. We show that in the case of pure, multiparticle quantum states, features of the global entanglement can already be extracted from local information alone. This is achieved by associating any given class of entanglement with an entanglement polytope—a geometric object that characterizes the single-particle states compatible with that class. Our results, applicable to systems of arbitrary size and statistics, give rise to local witnesses for global pure-state entanglement and can be generalized to states affected by low levels of noise.

Steganalyzing Images of Arbitrary Size with CNNs

2018 ◽  
Vol 2018 (7) ◽  
pp. 121-1-121-8 ◽  
Author(s):  
Clement Fuji Tsang ◽  
Jessica Fridrich
Keyword(s):  
Arbitrary Size

Variance prediction for pseudosystematic sampling on the sphere

2002 ◽  
Vol 34 (03) ◽  
pp. 469-483
Author(s):  
Ximo Gual-Arnau ◽  
Luis M. Cruz-Orive
Keyword(s):  
Fixed Point ◽  
Prediction Accuracy ◽  
Single Sample ◽  
Particle Model ◽  
Strict Sense ◽  
Biological Cell ◽  
Systematic Design ◽  
Arbitrary Size ◽  
Equal Area ◽  
Isotropic Random

Geometric sampling, and local stereology in particular, often require observations at isotropic random directions on the sphere, and some sort of systematic design on the sphere becomes necessary on grounds of efficiency and practical applicability. Typically, the relevant probes are of nucleator type, in which several rays may be contained in a sectioning plane through a fixed point (e.g. through a nucleolus within a biological cell). The latter requirement considerably reduces the choice of design in practice; in this paper, we concentrate on a nucleator design based on splitting the sphere into regions of equal area, but not of identical shape; this design is pseudosystematic rather than systematic in a strict sense. Firstly, we obtain useful exact representations of the variance of an estimator under pseudosystematic sampling on the sphere. Then we adopt a suitable covariogram model to obtain a variance predictor from a single sample of arbitrary size, and finally we examine the prediction accuracy by way of simulation on a synthetic particle model.

scholarly journals A Task-driven Grammar Refactoring Algorithm

10.14311/1636 ◽  
2012 ◽  
Vol 52 (5) ◽  
Author(s):  
Ivan Halupka ◽  
Ján Kollár ◽  
Emília Pietriková
Keyword(s):  
Programming Language ◽  
Structural Complexity ◽  
Computation Time ◽  
Medium Size ◽  
Specific Task ◽  
Arbitrary Size ◽  
Domain Specific ◽  
Context Free ◽  
Context Free Grammars

This paper presents our proposal and the implementation of an algorithm for automated refactoring of context-free grammars. Rather than operating under some domain-specific task, in our approach refactoring is perfomed on the basis of a refactoring task defined by its user. The algorithm and the corresponding refactoring system are called mARTINICA. mARTINICA is able to refactor grammars of arbitrary size and structural complexity. However, the computation time needed to perform a refactoring task with the desired outcome is highly dependent on the size of the grammar. Until now, we have successfully performed refactoring tasks on small and medium-size grammars of Pascal-like languages and parts of the Algol-60 programming language grammar. This paper also briefly introduces the reader to processes occurring in grammar refactoring, a method for describing desired properties that a refactored grammar should fulfill, and there is a discussion of the overall significance of grammar refactoring.

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