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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林永松(Yeong-Sung Lin) | |
| dc.contributor.author | Wei-Cheng Shih | en |
| dc.contributor.author | 石偉呈 | zh_TW |
| dc.date.accessioned | 2022-11-24T09:26:42Z | - |
| dc.date.available | 2022-11-24T09:26:42Z | - |
| dc.date.copyright | 2021-11-04 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-10-25 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/81749 | - |
| dc.description.abstract | 隨著第五代行動通訊網路 (5G) 架構被提出，軟體定義網路已成為實現 5G 網路的核心技術，藉由虛擬化技術可達成資源集中管理，使網路資源能夠有效地被動態配置，並發展出更具彈性與效率的網路架構。 基於 5G 網路的實現，網路切片所形成的虛擬邏輯網路已逐漸成為一種新興服務。然而隨著網路頻寬需求量以極快速度成長，網路服務供應商必須在有限資源內滿足客戶需求。因此本論文提出一種能夠有效優化網路傳輸效率及妥善配置軟體資源的演算法，同時採用等候理論、優先權機制、允入控制等通訊理論，達成 5G 網路中「擴增頻寬」、「低延遲」等規格標準。 我們將這個複雜的問題進一步轉換為數學規劃模型，目標為最大化整體系統收益，同時必須符合傳輸流量需求與延遲限制，並以拉格朗日鬆弛法為基礎設計演算法，目的在複雜維度的搜尋空間內找出近似最佳解，建立高效能且高頻寬之網路系統。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-24T09:26:42Z (GMT). No. of bitstreams: 1 U0001-2410202114113500.pdf: 6550928 bytes, checksum: d14ca9bb99fc12df75edde7815f63d8e (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 致謝 i 摘要 ii Abstract iii Contents iv List of Figures ix List of Tables xi Chapter 1 Introduction 1 1.1 Background 1 1.2 Motivation 3 1.3 Thesis Organization 4 Chapter 2 Literature Review 5 2.1 Network Function Virtualization and Software-Defined Network 5 2.2 OpenFlow Protocol 8 2.3 M / G / 1 Queueing Theory 9 2.3.1 Non-Preemptive Priority Queueing 10 2.3.2 Preemptive Priority Queueing 13 2.4 Admission Control 14 Chapter 3 Problem Formulation 16 3.1 Problem Description 16 3.2 Mathematical Formulation 18 3.2.1 Non-Preemptive Admission Control Model 19 3.2.2 Preemptive Admission Control Model 24 Chapter 4 Solution Approach 29 4.1 Lagrangian Relaxation Method 29 4.2 Solution Approach for the Primal Problem 31 4.2.1 Lagrangian Relaxation Problem of Non-Preemptive Admission Control Model 31 4.2.1.1 Subproblem 1 (related to decision variable λw) 35 4.2.1.2 Subproblem 2 (related to decision variable ywi) 36 4.2.1.3 Subproblem 3 (related to decision variable xp) 38 4.2.1.4 Subproblem 4 (related to decision variable hwl) 39 4.2.1.5 Subproblem 5 (related to decision variable awlk) 40 4.2.1.6 Subproblem 6 (related to decision variable swlk) 41 4.2.1.7 Subproblem 7 (related to decision variable glk) 42 4.2.1.8 Subproblem 8 (related to decision variable ρlk) 43 4.2.1.9 Subproblem 9 (related to decision variable γlk) 44 4.2.1.10 Subproblem 10 (related to decision variable τl) 47 4.2.1.11 Subproblem 11 (related to decision variable qlk) 48 4.2.1.12 Subproblem 12 (related to decision variable tlk) 49 4.2.1.13 Subproblem 13 (related to decision variable bwlk) 50 4.2.1.14 Subproblem 14 (related to decision variable fwl) 51 4.2.1.15 Subproblem 15 (related to decision variable dw) 52 4.2.1.16 Subproblem 16 (related to decision variable vw) 53 4.2.2 Lagrangian Relaxation Problem of Preemptive Admission Control Model 54 4.2.2.1 Subproblem 1 (related to decision variable λw) 57 4.2.2.2 Subproblem 2 (related to decision variable ywi) 58 4.2.2.3 Subproblem 3 (related to decision variable xp) 60 4.2.2.4 Subproblem 4 (related to decision variable hwl) 61 4.2.2.5 Subproblem 5 (related to decision variable awlk) 62 4.2.2.6 Subproblem 6 (related to decision variable swlk) 63 4.2.2.7 Subproblem 7 (related to decision variable glk) 64 4.2.2.8 Subproblem 8 (related to decision variable ρlk) 65 4.2.2.9 Subproblem 9 (related to decision variable γlk) 66 4.2.2.10 Subproblem 10 (related to decision variable βlk) 69 4.2.2.11 Subproblem 11 (related to decision variable tlk) 70 4.2.2.12 Subproblem 12 (related to decision variable bwlk) 71 4.2.2.13 Subproblem 13 (related to decision variable fwl) 72 4.2.2.14 Subproblem 14 (related to decision variable dw) 73 4.2.2.15 Subproblem 15 (related to decision variable vw) 74 4.2.3 Lagrangian Dual Problem and Subgradient Method 75 4.2.4 Getting Primal Feasible Solution 77 4.2.4.1 Getting Primal Feasible Solution 1 - FCFS 77 4.2.4.2 Getting Primal Feasible Solution 2 - Priority Exchange 78 4.2.4.3 Getting Primal Feasible Solution 3 - Dynamic Routing 79 4.2.4.4 Getting Primal Feasible Solution 4 - Bisection Search 81 4.2.4.5 Summary of Solution Approach 82 Chapter 5 Computational Experiments 83 5.1 Experiment Environment 83 5.2 Performance Metrics 86 5.3 Experiment Cases of Non-Preemptive Model 87 5.3.1 Case 1 : Number of QoS Levels Affects Reward 88 5.3.2 Case 2 : Performance Comparison of Different Heuristic Solutions regarding Number of QoS Levels 89 5.3.3 Case 3 : Performance Comparison of Different Heuristic Solutions regarding Traffic Rate 90 5.3.4 Case 4 : Performance Comparison of Different Heuristic Solutions regarding Delay 92 5.4 Experiment Cases of Preemptive Model 93 5.4.1 Case 1 : Number of QoS Levels Affects Reward 95 5.4.2 Case 2 : Performance Comparison of Different Heuristic Solutions regarding Number of QoS Levels 96 5.4.3 Case 3 : Performance Comparison of Different Heuristic Solutions regarding Traffic Rate 97 5.4.4 Case 4 : Performance Comparison of Different Heuristic Solutions regarding Delay 99 5.5 Comparison with Previous Generation Algorithm 101 5.6 Discussion of Experiment Results 102 Chapter 6 Conclusions and Future Work 104 6.1 Conclusions 104 6.2 Future Work 105 References 106 | |
| dc.language.iso | en | |
| dc.subject | 允入控制 | zh_TW |
| dc.subject | 拉格朗日鬆弛法 | zh_TW |
| dc.subject | 動態規劃 | zh_TW |
| dc.subject | 第五代行動通訊網路 | zh_TW |
| dc.subject | 軟體定義網路 | zh_TW |
| dc.subject | 網路切片 | zh_TW |
| dc.subject | 5G | en |
| dc.subject | Lagrangian Relaxation | en |
| dc.subject | Network Slicing | en |
| dc.subject | Admission Control | en |
| dc.subject | SDN | en |
| dc.title | 允入控制決策於軟體定義網路之最佳化資源協作演算法 | zh_TW |
| dc.title | A Near-Optimal Resource Orchestration Algorithm Based on Admission Control in Software-Defined Networks | en |
| dc.date.schoolyear | 109-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳建錦(Hsin-Tsai Liu),李家岩(Chih-Yang Tseng),黃彥男,呂俊賢 | |
| dc.subject.keyword | 第五代行動通訊網路,軟體定義網路,允入控制,網路切片,動態規劃,拉格朗日鬆弛法, | zh_TW |
| dc.subject.keyword | 5G,SDN,Admission Control,Network Slicing,Lagrangian Relaxation, | en |
| dc.relation.page | 109 | |
| dc.identifier.doi | 10.6342/NTU202104084 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2021-10-26 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
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