The Total Acquisition Number Of The Randomly Weighted Path

There exists a significant body of work on determining the acquisition number at(G) of various graphs when the vertices of those graphs are each initially assigned a unit weight. We determine properties of the acquisition number of the path, star, complete, complete bipartite, cycle, and wheel graph...

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Main Authors: Godbole Anant, Kelley Elizabeth, Kurtz Emily, Prałat Paweł, Zhang Yiguang
Format: Article
Language:English
Published: Sciendo 2017-11-01
Series:Discussiones Mathematicae Graph Theory
Subjects:
Online Access:https://doi.org/10.7151/dmgt.1972
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spelling doaj-18c5eb2b65144f5eb8a570c8a0f90bf12021-09-05T17:20:22ZengSciendoDiscussiones Mathematicae Graph Theory2083-58922017-11-0137491993410.7151/dmgt.1972dmgt.1972The Total Acquisition Number Of The Randomly Weighted PathGodbole Anant0Kelley Elizabeth1Kurtz Emily2Prałat Paweł3Zhang Yiguang4Department of Mathematics and Statistics East Tennessee State University, USADepartment of Mathematics University of Minnesota, Minnesota, USADepartment of Mathematics Wellesley College, USADepartment of Mathematics Ryerson University, USADepartment of Applied Mathematics and Statistics The Johns Hopkins University, USAThere exists a significant body of work on determining the acquisition number at(G) of various graphs when the vertices of those graphs are each initially assigned a unit weight. We determine properties of the acquisition number of the path, star, complete, complete bipartite, cycle, and wheel graphs for variations on this initial weighting scheme, with the majority of our work focusing on the expected acquisition number of randomly weighted graphs. In particular, we bound the expected acquisition number E(at(Pn)) of the n-path when n distinguishable “units” of integral weight, or chips, are randomly distributed across its vertices between 0.242n and 0.375n. With computer support, we improve it by showing that E(at(Pn)) lies between 0.29523n and 0.29576n. We then use subadditivity to show that the limiting ratio lim E(at(Pn))/n exists, and simulations reveal more exactly what the limiting value equals. The Hoeffding-Azuma inequality is used to prove that the acquisition number is tightly concentrated around its expected value. Additionally, in a different context, we offer a non-optimal acquisition protocol algorithm for the randomly weighted path and exactly compute the expected size of the resultant residual set.https://doi.org/10.7151/dmgt.1972total acquisition numberpoissonizationdepoissonizationmaxwell-boltzman and bose-einstein allocation.
collection DOAJ
language English
format Article
sources DOAJ
author Godbole Anant
Kelley Elizabeth
Kurtz Emily
Prałat Paweł
Zhang Yiguang
spellingShingle Godbole Anant
Kelley Elizabeth
Kurtz Emily
Prałat Paweł
Zhang Yiguang
The Total Acquisition Number Of The Randomly Weighted Path
Discussiones Mathematicae Graph Theory
total acquisition number
poissonization
depoissonization
maxwell-boltzman and bose-einstein allocation.
author_facet Godbole Anant
Kelley Elizabeth
Kurtz Emily
Prałat Paweł
Zhang Yiguang
author_sort Godbole Anant
title The Total Acquisition Number Of The Randomly Weighted Path
title_short The Total Acquisition Number Of The Randomly Weighted Path
title_full The Total Acquisition Number Of The Randomly Weighted Path
title_fullStr The Total Acquisition Number Of The Randomly Weighted Path
title_full_unstemmed The Total Acquisition Number Of The Randomly Weighted Path
title_sort total acquisition number of the randomly weighted path
publisher Sciendo
series Discussiones Mathematicae Graph Theory
issn 2083-5892
publishDate 2017-11-01
description There exists a significant body of work on determining the acquisition number at(G) of various graphs when the vertices of those graphs are each initially assigned a unit weight. We determine properties of the acquisition number of the path, star, complete, complete bipartite, cycle, and wheel graphs for variations on this initial weighting scheme, with the majority of our work focusing on the expected acquisition number of randomly weighted graphs. In particular, we bound the expected acquisition number E(at(Pn)) of the n-path when n distinguishable “units” of integral weight, or chips, are randomly distributed across its vertices between 0.242n and 0.375n. With computer support, we improve it by showing that E(at(Pn)) lies between 0.29523n and 0.29576n. We then use subadditivity to show that the limiting ratio lim E(at(Pn))/n exists, and simulations reveal more exactly what the limiting value equals. The Hoeffding-Azuma inequality is used to prove that the acquisition number is tightly concentrated around its expected value. Additionally, in a different context, we offer a non-optimal acquisition protocol algorithm for the randomly weighted path and exactly compute the expected size of the resultant residual set.
topic total acquisition number
poissonization
depoissonization
maxwell-boltzman and bose-einstein allocation.
url https://doi.org/10.7151/dmgt.1972
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