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Title page
Abstract
Contents
I. Introduction 15
II. Employed Heuristic Methods 19
2.1 Evolutionary computation algorithm 19
2.1.1 Generic algorithm 20
2.1.2 Coevolutionary algorithm 24
2.2 Tabu search 27
III. Route Selection and Rate Allocation in Multirate Multicast Networks 29
3.1 Problem overview and literature review 29
3.1.1 Problem overview 29
3.1.2 Literature review 32
3.2 Problem definition 37
3.2.1 Problem description 38
3.2.2 Problem formulation 40
3.3 Methods for receiver rate allocation and multicast tree generation 42
3.3.1 Decision rule for receiver rate allocation 42
3.3.2 Single multicast tree generation 43
3.3.3 Simultaneously multiple multicast trees generation with receiver rate allocation 46
3.4 Proposed evolutionary computation algorithms 47
3.4.1 Proposed simple genetic algotithm 48
A. Genetic representation and evaluation function 48
B. Selection scheme and genetic operators 49
C. Procedure of simple genetic algorithm 50
3.4.2 Proposed coevolutionary algorithm 51
A. Procedure of coevolutionary algorithm 51
B. Selection of environment individualsand fitness evaluation 53
C. Genetic presentation and genetic operators 54
3.5 Simulation design and results 55
3.5.1 Problem sets and parameter settings 55
3.5.2 Evaluation of performance 59
3.5.3 Performance analysis according to problem complexity 64
3.6 Conclusions 66
IV. Server Location and Storage Allocation in Multimedia-On-Demand Networks 68
4.1 Problem overview and previous studies on MOD optimization 68
4.2 Problem definition 74
4.2.1 MOD optimization ptoblem in a non-hierachical architecture 74
A. Problem description 74
B. Problem formulation 76
4.2.2 MOD optimization problem in a two-level-hierachical architecture 77
A. Problem description 77
B. Problem formualtion 79
4.3 Proposed heurisitc methods 82
4.3.1 Genetic Algorithm for MOD optimizatio problem in a non-hierarchical architecture 82
A. Genetic representation and evaluation function 82
B. Genetic operators and procedure of GA 83
4.3.2 Tabu Search for MOD optimization problem in a two-level hierarchicla architecture 83
A. Neighborhood structure 83
B. Search strategy 84
4.3.3 Genetic Algorithm for MOD optimization problem in a two-level hierarchical architecture 87
A. Genetic representation and evaluatio function 87
B. Genetic operators and procedure of GA 88
4.4 Simulation design and results 89
4.4.1 Problem sets and parameter settings 90
A. Problem sets and parameters for MOD optimizatin problem in a non-hierachical architecture 90
B. Problem sets and parameters for MOD optimization problem in a two-level hierarchical architecture 92
4.4.2 Evaluation of performance 94
A. Evaluation of performance for MOD optimization problem in a non-hierarchical architecture 94
B. Evaluation of performance for MOD optimization problem in a two-level hierarchical architecture 97
4.4.3 Characteristics analysis of factors related to al two-level hierarchical MOD network design 99
A. Costs analysis according to the number of programs stored in the LSs 100
B. Cost analysis according to changes of parameter values 101
C. The number of installed servers according to demand fluctuation among COs 103
4.4.4 Resource management in a two-level hierarchical MOD network 105
4.5 Conclusions 107
V. Power Control for Radio Resource Management in CDMA Cellular Radio Networks 108
5.1 Problem overview and prior research on power control 108
5.2 Cellular CDMA distributed and constrained power control system models 110
5.2.1 Distributed power control model 110
5.2.2 Constrained power control model 112
5.2.3 IS-95 and W-CDMA system power control model 112
5.3 Proposed power control algorithm 113
5.4 Simulation design and results 115
5.4.1 Simulation design 115
5.4.2 Simulation results 117
5.5 Conclusions 118
VI. Conclusions 120
6.1 Summary and contributions 120
6.2 Limitations and further study 122
국문요약 123
References 126
Acknowledgements 132
[Table 3-1] The number of 2nd-layer nodes connected with 1st-layer nodes 57
[Table 3-2] Problem parameter settings for the multirate multicast networks 58
[Table 3-3] Problem set for the multirate multicast networks 58
[Table 3-4] Parameters for the proposed algorithm (simple GA and Co-EA) 59
[Table 3-5] Performance comparison of the hierachical approach and the proposed methods 61
[Table 3-6] Results of statistical analysis for A-12 problem 63
[Table 3-7] Results of stastical analysis for B-11 problem 63
[Table 3-8] Results of stastical analysis for D-32 problem 64
[Table 4-1] Problem parameter setting for MOD optimization problem in a non-hierarchical architecture 90
[Table 4-2] Problem set for MOD optimization problem in a non-hierarchical architecture 91
[Table 4-3] Parameters for the proposed GA in a non-hierarchical architecture 91
[Table 4-4] Problem parameters setting for MOD optimization problem in a two-level hierarchical architecture 92
[Table 4-5] Problem set for MOD optimization problem in a two-level hierarchical architecture 93
[Table 4-6] Parameters for the proposed TS 93
[Table 4-7] Parameters for the proposed GA in a two-level hierarchical architecture 94
[Table 4-8] Performance comparison between Enumeration and GA 95
[Table 4-9] Performance analysis of the proposed method 97
[Table 4-10] Performance comparison among Enumeration, TS and GA 98
[Table 4-11] Results of design for relatively large MOD networks 99
[Table 4-12] Storage amount of programs stored in each LS and the number of programs stored in the LSs 105
[Table 4-13] Total cost, the location of LSs and the number of programs stored in LSs 106
[Table 5-1] Parameters for the proposed GA-based EC algorithm 116
[Figure 2-1] Neighborhood structure 22
[Figure 2-2] Two-point crossover 23
[Figure 2-3] Procedure of the primary proposed GA 24
[Figure 2-4] Pop-C and Pop-S 25
[Figure 3-1] An example of two multicast trees 39
[Figure 3-2] Multicast routing with two link types 45
[Figure 3-3] Modified 2-point crossover for CBT method 49
[Figure 3-4] Modified order crossover operator 50
[Figure 3-5] Inversion operator 50
[Figure 3-6] Various network topologies 56
[Figure 3-7] Layered network topology 57
[Figure 3-8] Change trend of improvements ratio according to the size of bandwidth 65
[Figure 3-9] Change trend of miprovement ration accordigng to the number of upper bound of link delay 66
[Figure 4-1] A non-hierarchical MOD network 75
[Figure 4-2] A two level-hierarchical MOD network 78
[Figure 4-3] Procedure of the proposed TS 86
[Figure 4-4] Modified 2-point crossoverfor MOD optimization in a two-level hierarchical architecture 88
[Figure 4-5] Procedure of the proposed GA for MOD optimization problems in a two-level hiercrchical architecture 89
[Figure 4-6] Results in the case of 10 Cos 96
[Figure 4-7] Results in the case of 20 COs 96
[Figure 4-8] Cost change trends according to the number of programs stored in the LSs 101
[Figure 4-9] Cost change trends according to the number of multiple accesses 102
[Figure 4-10] Cost change trends accordign to the difference of preference ration 103
[Figure 4-11] Number analysis of installed servers according to demand fluctuatio amogn COs 104
[Figure 4-12] Total amount of programs stored in each LS 106
[Figure 5-1] Gain of the DS-CDMA link between mobile terminals and base stations 111
[Figure 5-2] Procedure of the proposed GA-based EC algorithm 115
[Figure 5-3] Supportable rate at the upper graphs and power level with W unit at the lower graphs accordign to the system congestion 117
[Figure 5-4] Supportable rate at the upper graphs and power level with W unit at the lower graphs according to the level of communication quality 118
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