Title
Parallel Genetic Programming: Component Object-based Distributed Collaborative Approach
Abstract
We discuss the feasibility of applying the distributed collaborative approach for improving the computational performance of genetic programming (GP), implemented on cost-efficient clusters or the Internet. The proposed approach exploits the coarse grained inherent parallelism in GP among relatively autonomous subpopulations. The developed architecture of a distributed collaborative parallel GP (DCPGP) features a single, global migration broker and centralized manager of the semi-isolated subpopulations, which contribute to quick propagation of the globally fittest individuals among the subpopulations; this reduces the performance demands on the underlying communication network, and achieves dynamic scaling-up features. DCPGP exploits the distributed component object model (DCOM) as a communication paradigm, which as a true system model offers generic support for the issues of naming, locating and security of communicating entities of the developed architecture. Experimentally obtained speedup results show that close to linear speedup characteristics of the prototype of DCPGP are achieved on a network of 8 workstations
Year
DOI
Venue
2001
10.1109/ICOIN.2001.905345
Beppu City, Oita
Keywords
Field
DocType
component object model,linear speedup characteristic,semi-isolated subpopulations,collaborative approach,developed architecture,computational performance,collaborative parallel gp,communication paradigm,parallel genetic programming,autonomous subpopulations,prototypes,genetic programming,groupware,communication networks,distributed component object model,distributed computing,parallel programming,dcom,cost efficiency,communication network,internet,system modeling,computer architecture,parallel processing,genetic algorithms
Telecommunications network,Computer science,Collaborative software,Computer network,Workstation,Genetic programming,Distributed Component Object Model,System model,Genetic algorithm,Distributed computing,Speedup
Conference
ISBN
Citations 
PageRank 
0-7695-0951-7
4
0.47
References 
Authors
4
3
Name
Order
Citations
PageRank
Ivan Tanev127846.51
Takashi Uozumi2437.58
Koichi Ono3584.84