Titlebook: Combinatorial and Algorithmic Aspects of Networking; First Workshop on Co Alejandro López-Ortiz,Angèle M. Hamel Conference proceedings 2005

夜晚

Paul Christoph Gembarski,Roland Lachmayer this paper, we consider the problem of how to obtain a prescribed level of connectivity with a minimum number of nodes connecting to the external network..Let . = (.,.) be a digraph. A subset?. of vertices in?. may be chosen, the so-called external vertices. An internal path is a normal directed pa

placebo-effect

Volker Nissen,Torsten Gollhardtegree distribution, average distance), it is based on some real-world observations, and it is sufficiently simple to make it possible to prove its main properties. This model consists in sampling a random bipartite graph with prescribed degree distribution. Indeed, we show that any can be viewed as

Gentry

Jan-Hendrik Heinen,Jens P?ppelbu? to introduce uncontrolled sampling biases that might produce statistical properties of the sampled graph which sharply differ from the original ones. Here we explore these biases and provide a statistical analysis of their origin. We derive a mean-field analytical approximation for the probability

Embolic-Stroke

碌碌之人

Introduction to Smart Service Designontrivial, and complex data structures make an important contribution in this regard. This article surveys the three main approaches to the problem and investigates the associated data structures and algorithms. We also explore variations on these approaches and conclude with a discussion of current

Pelago

中世紀(jì)

0302-9743 Overview: 978-3-540-27873-3978-3-540-31860-6Series ISSN 0302-9743 Series E-ISSN 1611-3349

知道

https://doi.org/10.1007/978-3-642-37006-9 finds a Hamiltonian cycle in . with high probability when ., and terminates in linear worst-case number of pulses, and in expected .(..) pulses. The algorithm requires, in each node of the network, only .(.) space and .(.) internal instructions.

Forage飼料

Introduction to Smart Service Designontrivial, and complex data structures make an important contribution in this regard. This article surveys the three main approaches to the problem and investigates the associated data structures and algorithms. We also explore variations on these approaches and conclude with a discussion of current trends.

FUME

A Distributed Algorithm to Find Hamiltonian Cycles in , Random Graphs finds a Hamiltonian cycle in . with high probability when ., and terminates in linear worst-case number of pulses, and in expected .(..) pulses. The algorithm requires, in each node of the network, only .(.) space and .(.) internal instructions.