eprintid: 3551
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/35/51
datestamp: 2023-11-09 15:51:48
lastmod: 2023-11-09 15:51:48
status_changed: 2023-11-09 15:47:04
type: article
metadata_visibility: show
creators_name: Zakaria, N.
creators_name: Pal, A.J.
creators_name: Shah, S.N.M.
title: Stagewise optimization of distributed clustered finite difference time domain (FDTD) using genetic algorithm
ispublished: pub
keywords: cluster; distribution; Finite -difference time domains (FDTD); hybrid; Hybrid genetic algorithms; Optimization procedures; optimized; Stagewise optimizations, Finite difference time domain method; Optimization; Personal computers, Genetic algorithms
note: cited By 4
abstract: In this paper, we explore the use of hybrid genetic algorithm for optimized clustering and distribution of Finite Difference Time Domain (FDTD) computation over a large number of desktop computers and servers. Given a large number of computers, we first attempt to compute an optimal set of clusters. The clustering takes into consideration similarity of machine capability plus the interconnection speed. It considers as well the predicted availability pattern for each computer. Then, for each cluster, we optimize the distribution of FDTD workload over its computers. Hence, the overall optimization procedure optimizes clustered distributed FDTD. We show in this paper how pure as well as hybrid genetic algorithm can effectively be used to perform the optimization. © 2013 ICIC International.
date: 2013
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880069910&partnerID=40&md5=2934c6d7b08141aba5295b259d994966
full_text_status: none
publication: International Journal of Innovative Computing, Information and Control
volume: 9
number: 6
pagerange: 2303-2326
refereed: TRUE
issn: 13494198
citation:   Zakaria, N. and Pal, A.J. and Shah, S.N.M.  (2013) Stagewise optimization of distributed clustered finite difference time domain (FDTD) using genetic algorithm.  International Journal of Innovative Computing, Information and Control, 9 (6).  pp. 2303-2326.  ISSN 13494198