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| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 林永松(Yeong-Sung Lin) | |
| dc.contributor.author | Wei-Chih Cheng | en |
| dc.contributor.author | 鄭惟之 | zh_TW |
| dc.date.accessioned | 2021-06-08T02:13:27Z | - |
| dc.date.copyright | 2020-08-20 | |
| dc.date.issued | 2020 | |
| dc.date.submitted | 2020-08-17 | |
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Lin, “DFDP: A Distributed Algorithm for Finding Disjoint Paths in Wireless Sensor Networks with Correctness Guarantee,” International Journal of Distributed Sensor Networks, pp.1-11, Jun. 2014. [19] M. H. Dahshan, “Maximum-Bandwidth Node-Disjoint Paths,” International Journal of Advanced Computer Science and Applications (IJACSA), vol. 3, no. 3, pp. 48-56, Mar. 2012. [20] M. L. Fisher, “The Lagrangian Relaxation Method for Solving Integer Programming Problems,” Management Science, vol. 50, no. 12, pp. 1861-1871, Dec. 2004. [21] A. M. Geoffrion, “Lagrangean Relaxation for Integer Programming,” in Approaches to Integer Programming, M. L. Balinski, Eds. Berlin: Springer, 1974, pp. 82-114. [22] J. Y. Yen, “Finding the K Shortest Loopless Paths in a Network,” Management Science, vol. 17, no. 11, pp. 712–716, Jul. 1971. [23] M. Held and R. M. Karp, “The Traveling-Salesman Problem and Minimum Spanning Trees,” Operation Research, vol. 18, no. 6, pp. 1138-1162, Dec. 1970. [24] M. Held and R. M. Karp, “The Traveling-Salesman Problem and Minimum 90 Spanning Trees: Part II,” Mathematical Programming: Series A and B, vol. 1, no. 1, pp. 6-25, Dec. 1971. [25] M. Held, P. Wolfe, and H. P. Crowder, “Validation of Subgradient Optimization,” Mathematical Programming, vol. 6, no. 1, pp. 62-88, Dec. 1974. [26] R. Bhandari, “Suurballe’s disjoint pair algorithms,” Survival Networks: Algorithms for Diverse Routing, Springer-Verlag, pp.86-91, 1999. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/19687 | - |
| dc.description.abstract | 第五代行動通訊網路 (5G) 藉由軟體定義網路、網路功能虛擬化，以及網路切片等技術，使得實體網路設施得以虛擬化，讓網路之管理與擴充更為彈性，且能劃分成不同服務，將有助於滿足5G多樣化之需求與垂直應用。 本論文聚焦於組織內之5G網路，且資料經過加密之即時通訊垂直網路切片。然而，通訊的可靠度極為重要，為確保通訊過程不會因故中斷之服務品質，基於此需求，我們提出了一個數學規劃模型，在滿足高可靠度、高安全性、低延遲的情況下，以最小成本為目標建置出網路切片，希冀能提供決策建議給廠商或承租人參考，以作為較佳之資源規劃與佈建之依據。 我們將此複雜之問題以數學模型表示，目標為最小化建置成本，並且使用拉格朗日鬆弛法來解此問題，並開發了一個演算法來求得可行解，並藉由一系列的實驗證實此演算法具有最佳化網路資源規劃與建置的效能。 | zh_TW |
| dc.description.abstract | With the help of SDN, NFV, and network slicing, the 5G network can virtualize physical networks into isolated logical networks, which makes the management and extension of network more agile and effective. Therefore, it is more likely to satisfy the goals of 5G, which is diverse applications and vertical industries. Focusing on a network slicing of instant messaging in an organization which requires data encryption and high reliability, the fluent transmission is vital for ensuring uninterrupted transportation. Based on these considerations, we proposed an optimization deployment model, which deploys the network slicing with minimum cost and meanwhile ensures high security, high reliability, and low delay. We hope to provide the industry segments and tenants a reference for better service planning and purchase decisions. The complex problem is formulated to a mathematical model and solved optimally by using the Lagrangian relaxation method. Besides, we develop a Lagrangian relaxation based approach for getting feasible solutions. In the end, the proposed approach is validated by computational experiments to be effectively to optimally deploy a network slicing that satisfies economic efficiency, high reliability, high security, and quality of service (QoS). | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T02:13:27Z (GMT). No. of bitstreams: 1 U0001-1508202017485200.pdf: 3916817 bytes, checksum: 5a3b9402b698e78f30643eeeff72c7f0 (MD5) Previous issue date: 2020 | en |
| dc.description.tableofcontents | 誌謝 i 中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES viii LIST OF TABLES x Chapter 1 Introduction 1 1.1. Background 1 1.2. Motivation 4 1.3. Thesis Organization 5 Chapter 2 Literature Review 6 2.1. SDN 6 2.2. NFV 8 2.3. Disjoint Path 10 Chapter 3 Problem Formulation 14 3.1. Problem Description 14 3.2. Mathematical Formulation 18 3.2.1 Primal Problem 26 3.2.1.1. Objective Function 30 3.2.1.2. Capacity Constraints 30 3.2.1.3. Disjoint Path Constraints 31 3.2.1.4. Assignment Constraints 31 3.2.1.5. Delay Constraints 32 Chapter 4 Solution Approach 33 4.1. The Lagrangian Relaxation Method 33 4.2. Solution Approach for the Primal Problem 36 4.2.1. The Lagrangian Relaxation Problem 36 4.2.1.1. Subproblem 1 (related to decision variable ) 41 4.2.1.2. Subproblem 2 (related to decision variable ) 42 4.2.1.3. Subproblem 3 (related to decision variable ) 43 4.2.1.4. Subproblem 4 (related to decision variable ) 44 4.2.1.5. Subproblem 5 (related to decision variable ) 46 4.2.1.6. Subproblem 6 (related to decision variable and ) 47 4.2.1.7. Subproblem 7 (related to decision variable and ) 50 4.2.1.8. Subproblem 8 (related to decision variable and ) 52 4.2.1.9. Subproblem 9 (related to decision variable and ) 54 4.2.1.10. Subproblem 10 (related to decision variable and ) 56 4.2.1.11. Subproblem 11 (related to decision variable ) 58 4.2.1.12. Subproblem 12 (related to decision variable and ) 59 4.2.1.13. Subproblem 13 (related to decision variable ) 62 4.2.2. The Dual Problem and the Subgradient Method 70 4.2.3. Getting Primal Feasible Solution 73 4.2.4. Summary of Solution Approach 78 Chapter 5 Computational Experiments 82 5.1. Experiment Environment 82 5.2. Performance Metrics 88 5.3. Experiment Scenarios and Results 89 5.3.1. Case 1: Increasing Demand 93 5.3.2. Case 2: Increasing End-to-End Delay 94 5.3.3. Case 3: Increasing Required Path Number 95 5.3.4 Case 4: Performance of Suurballe’s and Yen’s Algorithm 98 5.3.5 Case 5: Cost Structure 100 5.3.6 Scalability Report 100 5.4. Discussion of Experiment Results 101 Chapter 6 Conclusions and Future Work 102 6.1. Conclusions 102 6.2. Future Work 103 6.2.1 The Operation Phase of The Network Slicing 103 6.2.2 The Computation of Required Number of Paths 103 6.2.3 Vulnerability of Attacks 105 REFERENCES 106 | |
| dc.language.iso | en | |
| dc.title | 於軟體定義網路中以最佳化技術為基礎之高可靠高安全且高效能資源協作演算法 | zh_TW |
| dc.title | An Optimization Based Resource Orchestration Algorithm to Achieve High Reliability and Security with QoS Assurance in Software Defined Networks | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 孔令傑(Ling-Chieh Kung),莊東穎(Tung-Ying Chuang),鍾順平(Shun-Ping Chung),呂俊賢(Chun-Hsien Lu) | |
| dc.subject.keyword | 第五代通訊移動系統,網路切片,網路協作,垂直應用,資源規劃,服務品質,多條不相交路徑,拉格朗日鬆弛法, | zh_TW |
| dc.subject.keyword | 5G,Network Slicing,Network Orchestration,Vertical Industry,Deployment,Quality of Service (QoS),K-Shortest Disjoint Paths,Lagrangian Relaxation, | en |
| dc.relation.page | 110 | |
| dc.identifier.doi | 10.6342/NTU202003532 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2020-08-18 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| Appears in Collections: | 資訊管理學系 | |
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| File | Size | Format | |
|---|---|---|---|
| U0001-1508202017485200.pdf Restricted Access | 3.83 MB | Adobe PDF |
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