RESEARCH ON RESOURCES SCHEDULING METHOD BASE ON SWARM INTELLIGENCE OPTIMAL ALGORITHM IN CLOUD COMPUTING ENVIRONMENT
Hongwei Zhao
Shenyang University
Copyright © 2017 by Cayley Nielson Press, Inc.
ISBN: 978-0-9992443-0-2
Cayley Nielson Press Scholarly Monograph Series Book Code No.: 140-1-1
US$125.50
Preface
Contents
1 Research on Multiple Particle Swarm Algorithm Based on Bacterial Swarming Behavior 8
1.1 Introduction.......................................................................................................................... 8
1.2 Particle Swarm Optimization..................................................................................... 10
1.3 MPSOBS Algorithm.......................................................................................................... 11
1.3.1 The Proposed Multiple Particle Swarm optimization algorithm based on Bacterial Swarming 12
1.3.2 The MPSOBS algorithm steps.................................................................................. 14
1.4 Benchmark Test................................................................................................................ 15
1.4.1 Test Function and Parameters................................................................................ 15
1.4.2 Simulation results for benchmark functions.................................................... 16
1.5 Conclusions......................................................................................................................... 20
1.6 Acknowledgments........................................................................................................... 21
2 Adaptive Resource Schedule Method in Cloud Computing System Based on Improved Artificial Fish Swarm..... 22
2.1 Introduction....................................................................................................................... 22
2.2 Related works.................................................................................................................... 24
2.3 Optimized AFS Algorithm............................................................................................. 27
2.3.1 The original AFS algorithm....................................................................................... 27
2.3.2 The Food Marks Artificial Fish Swarm (FMAFS) Algorithm...................... 28
2.4 Benchmark Tests.............................................................................................................. 32
2.4.1 Benchmark functions................................................................................................. 32
2.4.2 Parameter settings....................................................................................................... 32
2.4.3 Simulation results for benchmark functions.................................................... 34
2.4.4 Resource Schedule Algorithm Based on FMAFS Model................................ 36
2.5 Conclusion........................................................................................................................... 37
2.6 Acknowledgments........................................................................................................... 38
3 Optimization of Resource Schedule Based on Improved Particle Swarm Algorithm in Cloud Computing Environment...... 39
3.1 Introduction....................................................................................................................... 39
3.2 2. Related works............................................................................................................... 41
3.3 Resource Scheduling Base Particle Swarm Optimization.............................. 43
3.3.1 Particle Swarm Optimization................................................................................. 43
3.3.2 Improved particle swarm optimization algorithm DPSO.......................... 44
3.4. Benchmark Test............................................................................................................... 45
3.4.1 Test Function and Parameters................................................................................ 45
3.4.2 Simulation results for benchmark functions.................................................... 47
3.5 Conclusions......................................................................................................................... 49
3.6 Acknowledgments........................................................................................................... 50
4 Study of Artificial Fish Swarm algorithm Based on Coevolutionary for Hybrid Clustering 51
4.1 Introduction....................................................................................................................... 51
4.2 Materials Optimized AFS Algorithm and Methods............................................. 54
4.2.1 The original AFS algorithm....................................................................................... 54
4.2.2 The cooperative artificial fish swarm (CAFS) algorithm............................ 56
4.3 Benchmark Tests.............................................................................................................. 59
4.3.1 Benchmark functions................................................................................................. 59
4.3.2 Parameter settings....................................................................................................... 60
4.3.3 Simulation results for benchmark functions.................................................... 62
4.4 A Hybrid Clustering Algorithm Based on CAF Clustering Model.................. 63
4.5 Data Clustering Experimental Results..................................................................... 65
4.5.1 Experiment by Simulation data sets..................................................................... 66
4.5.2 Experiment by real data sets................................................................................... 68
4.6 Conclusion........................................................................................................................... 69
4.7 Acknowledgment............................................................................................................. 70
5 A Dynamic Dispatching Method of Resource based on Particle swarm optimization for Cloud Computing Environment..... 71
5.1 Introduction....................................................................................................................... 71
5.2 Related works.................................................................................................................... 73
5.3 Scheduling system of Cloud Computing................................................................. 74
5.3.1 Particle Swarm Optimization................................................................................. 74
5.3.2 Layered scheduling system architecture........................................................... 76
5.3.3 Load balancing principle........................................................................................... 78
5.3.4 The realization of resource distribution algorithm used Layered scheduling system 79
5.4 Experiment and the analysis of results................................................................... 81
5.5 Conclusion........................................................................................................................... 83
6 A PSO-Based Resource Scheduling Strategy for Load Balancing in Cloud Computing 84
6.1. Introduction...................................................................................................................... 84
6.2 Related works.................................................................................................................... 86
6.3 Scheduling system of Cloud Computing................................................................. 87
6.3.1 Particle Swarm Optimization................................................................................. 87
6.3.2 Layered scheduling system architecture........................................................... 89
6.3.3 Load balancing principle........................................................................................... 90
6.3.4 The realization of resource distribution algorithm used Layered scheduling system 91
6.4 Experiment and the analysis of results................................................................... 91
6.5 Conclusions......................................................................................................................... 92
6.6 Acknowledgment............................................................................................................. 93
7 A Novel Modified Differential Evolution Algorithm for Clustering 94
7.1 Introduction....................................................................................................................... 94
7.2 Differential Evolution Algorithm.............................................................................. 96
7.3 Modified differential evolution algorithm............................................................ 97
7.4 Experimental results and analysis............................................................................ 99
7.4.1 Maintenance-free benchmark functions......................................................... 100
7.4.2 Results for the 20-D problems............................................................................. 101
7.5 Conclusions...................................................................................................................... 103
7.6 Acknowledgments........................................................................................................ 104
8 Resource Schedule Algorithm Based on Artificial Fish Swarm in Cloud Computing Environment...... 105
8.1 Introduction..................................................................................................................... 105
8.2 Related works................................................................................................................. 107
8.3 Scheduling system of Cloud Computing.............................................................. 108
8.3.1 Description of the Basic Behaviors of AFSA................................................... 108
8.3.2 Improvement of AFSA............................................................................................. 110
8.3.3 Layered scheduling system architecture......................................................... 111
8.3.4 The realization of resource distribution algorithm used Layered scheduling system 113
8.4 Experiment and the analysis of results................................................................ 114
8.5 Conclusion........................................................................................................................ 116
8.6 Acknowledgements...................................................................................................... 116
9 Research on Multiple Particle Swarm Algorithm Based on Analysis of Scientific Materials 117
9.1 Introduction..................................................................................................................... 117
9.2 Basic flow of PSO algorithm..................................................................................... 118
9.3 PSO algorithm related control parameters........................................................ 119
9.4 The Proposed Multiple Particle Swarm optimization algorithm............. 122
9.5 Summary........................................................................................................................... 123
9.6 Acknowledgment.......................................................................................................... 123
References............................................................................................ 124
Readership
This book should be useful for students, scientists, engineers and professionals working in the areas of optoelectronic packaging, photonic devices, semiconductor technology, materials science, polymer science, electrical and electronics engineering. This book could be used for one semester course on adhesives for photonics packaging designed for both undergraduate and graduate engineering students.
