Solutions to Parallel and Distributed Computing Problems Lessons from Biological Sciences

by Zomaya, Albert Y.; Ercal, Fikret; Olariu, Stephan

• ISBN13: 9780471353522
• ISBN10: 0471353523
• Edition: 1st
• Format: Hardcover
• Copyright: 2000-11-14
• Publisher: Wiley-Interscience

Summary

* Applying neural networks for problem solving in wireless communication systems

Author Biography

ALBERT Y. ZOMAYA, PhD, is a professor at the University of Western Australia, Perth, Australia.<BR>

Table of Contents

Contributors	ix
Preface	xi
Distributed Cellular Automata: Large-Scale Simulation of Natural Phenomena	1	(46)
P. M. A. Sloot
J. A. Kaandorp
A. G. Hoekstra
B. J. Overeinder
Introduction	1	(3)
Background of Cellular Automata Concepts	4	(8)
Execution Models for Cellular Automata	12	(5)
Cellular Automata as Models for Fluid Flow	17	(8)
Selected Applications	25	(16)
Summary	41	(6)
Parallel Implementations of Evolutionary Algorithms	47	(22)
Hartmut Schmeck
Jurgen Branke
Udo Kohlmorgen
Introduction	47	(1)
Standard Approaches to Parallelizing Evolutionary Algorithms	48	(6)
Parallel Global Selection	54	(2)
Setup for Experimental Investigation	56	(2)
Test Problems	58	(2)
Discussion of Results	60	(6)
Summary	66	(3)
Toward Hybrid Biologically Inspired Heuristics	69	(18)
El-Ghazali Talbi
Introduction	69	(1)
Design Issues	70	(8)
Implementation Issues	78	(2)
A Grammar for Extended Hybridization Schemes	80	(2)
Summary	82	(5)
Nature-Inspired Optimization Algorithms for Parallel Simulations	87	(24)
Azzedine Boukerche
Sajal K. Das
Introduction	87	(1)
What Is Parallel Simulation?	88	(3)
Previous and Related Work	91	(2)
Simulated Annealing: Conservative Partitioning	93	(5)
Genetic Algorithm: Optimistic Load Balancing	98	(4)
Stochastic Learning Automata	102	(4)
Summary	106	(5)
An Introduction to Genetic-Based Scheduling in Parallel Processor Systems	111	(24)
Albert Y. Zomaya
Richard C. Lee
Stephan Olariu
Introduction	111	(1)
Task Scheduling and Problem Formulation	112	(7)
The Proposed Approach	119	(9)
Case Studies	128	(3)
Summary	131	(4)
Mapping Tasks onto Distributed Heterogeneous Computing Systems Using a Genetic Algorithm Approach	135	(44)
Mitchell D. Theys
Tracy D. Braun
Yu-Kwong Kwok
Howard Jay Siegel
Anthony A. Maciejewski
Introduction	135	(2)
Problem Descriptions	137	(3)
Genetic Algorithm Overview	140	(1)
Static Matching and Scheduling of Subtasks	141	(15)
Semistatic Matching and Scheduling of Subtasks	156	(9)
Static Matching and Scheduling for Meta-Tasks	165	(9)
Summary	174	(5)
Evolving Cellular Automata-Based Algorithms for Multiprocessor Scheduling	179	(30)
F. Seredynski
Introduction	179	(1)
Multiprocessor Scheduling	180	(2)
Cellular Automata	182	(3)
The Concept of the CA-Based Scheduler	185	(2)
Defining Local Neighborhood	187	(6)
CA-Based Scheduler	193	(2)
Experiments	195	(10)
Summary	205	(4)
Parallel Task Mapping with Biological Computing Models	209	(22)
Tarek El-Ghazawi
Ophir Frieder
Jaafar Gaber
Salim Alaoui
Introduction	209	(1)
The Task-Mapping Problem	210	(1)
Genetic Algorithms	211	(3)
Parallel Genetic Algorithms	214	(2)
Task Mapping with Genetic Algorithms	216	(6)
Discussion	222	(1)
Task Mapping with Neural Networks	223	(5)
Summary	228	(3)
Scheduling Parallel Programs Using Genetic Algorithms	231	(24)
Ishraq Ahmad
Yu-Kwong Kwok
Imtiaz Ahmad
Muhammad Dhodhi
Introduction	231	(2)
Static Scheduling of Parallel Programs to Message-Passing Architectures	233	(5)
Overview of Genetic Algorithms	238	(1)
Scheduling Tasks to a Homogeneous System	239	(6)
Scheduling Tasks to a Heterogeneous System	245	(7)
Summary	252	(3)
Applications of Neural Networks to Mobile Communication Systems	255	(14)
Azzedine Boukerche
Mirela Sechi M. Notare
Introduction	255	(1)
Neural-Network Definition	256	(2)
Adaptive Equalizer for Digital Mobile-Radio Channels	258	(2)
Channel Assignment in Mobile-Radio Systems	260	(1)
Neural Networks Applied to the Channel-Assignment Problem	261	(1)
GSM Radio Resource~Management	261	(1)
Neural Fraud Detection in Mobile-Phone Systems	262	(4)
Summary	266	(3)
Index	269