Broadcasting is an information dissemination problem
in which a message originating at one node of a
communication network (modeled as a graph) is to be
sent to all other nodes as quickly as possible. This
paper describes a new way of producing broadcasting
schemes using genetic programming. This technique has
proven successful by easily finding optimal algorithms
for several well-known families of networks (grids,
hypercubes and cycle connected cubes) and has indeed
generated a new scheme for butterflies that improves
the known upper bound for the broadcasting time of
these networks.
GPQUICK. Tried on 4 problems (5x5 directed grid,
torroidal, hypercube, cube connected cycles) finds
known optima.
"5.5 Butterfly graph For these graphs no optimal
broadcasting algorithm is known... we improve the upper
bound to BF_k 2k-2" for k=7,8...16
%0 Journal Article
%1 Comellas:1998:GPD
%A Comellas, F.
%A Giménez, G.
%D 1998
%J Parallel Processing Letters
%K algorithms, broadcasting, butterfly genetic graph networks, programming,
%N 4
%P 549--560
%T Genetic Programming to Design Communication Algorithms
for Parallel Architectures
%U http://www-mat.upc.es/~comellas/genprog/genprog.html
%V 8
%X Broadcasting is an information dissemination problem
in which a message originating at one node of a
communication network (modeled as a graph) is to be
sent to all other nodes as quickly as possible. This
paper describes a new way of producing broadcasting
schemes using genetic programming. This technique has
proven successful by easily finding optimal algorithms
for several well-known families of networks (grids,
hypercubes and cycle connected cubes) and has indeed
generated a new scheme for butterflies that improves
the known upper bound for the broadcasting time of
these networks.
@article{Comellas:1998:GPD,
abstract = {Broadcasting is an information dissemination problem
in which a message originating at one node of a
communication network (modeled as a graph) is to be
sent to all other nodes as quickly as possible. This
paper describes a new way of producing broadcasting
schemes using genetic programming. This technique has
proven successful by easily finding optimal algorithms
for several well-known families of networks (grids,
hypercubes and cycle connected cubes) and has indeed
generated a new scheme for butterflies that improves
the known upper bound for the broadcasting time of
these networks.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Comellas, F. and Gim{\'e}nez, G.},
bibdate = {Mon Nov 09 07:22:43 1998},
biburl = {https://www.bibsonomy.org/bibtex/2c78785f6a8fb5cc2506ae8cc1ad51645/brazovayeye},
coden = {PPLTEE},
interhash = {cc00102acf1b754a7ad0d471cb984adb},
intrahash = {c78785f6a8fb5cc2506ae8cc1ad51645},
issn = {0129-6264},
journal = {Parallel Processing Letters},
keywords = {algorithms, broadcasting, butterfly genetic graph networks, programming,},
notes = {GPQUICK. Tried on 4 problems (5x5 directed grid,
torroidal, hypercube, cube connected cycles) finds
known optima.
{"}5.5 Butterfly graph For these graphs no optimal
broadcasting algorithm is known... we improve the upper
bound to BF_k \le 2k-2{"} for k=7,8...16},
number = 4,
pages = {549--560},
size = {12 pages},
timestamp = {2008-06-19T17:38:04.000+0200},
title = {Genetic Programming to Design Communication Algorithms
for Parallel Architectures},
url = {http://www-mat.upc.es/~comellas/genprog/genprog.html},
volume = 8,
year = 1998
}