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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 | Ya-Syuan Wu | en |
| dc.contributor.author | 吳亞璇 | zh_TW |
| dc.date.accessioned | 2021-05-19T17:40:28Z | - |
| dc.date.available | 2029-08-07 | |
| dc.date.available | 2021-05-19T17:40:28Z | - |
| dc.date.copyright | 2019-08-19 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-08-07 | |
| dc.identifier.citation | [1] Statista. (2018). Mobile Internet - Statistics & Facts. [Online]. Available: https://www.statista.com/topics/779/mobile-internet/ [Accessed: Nov. 20, 2018].
[2] Statista. (2018). Global Mobile Data Traffic from 2017 to 2022 (in Exabytes per Month). [Online]. Available: https://www.statista.com/statistics/271405/global-mobile-data-traffic-forecast/ [Accessed: Nov. 20, 2018]. [3] “IMT Vision – Framework and Overall Objectives of the Future Development of IMT for 2020 and Beyond,” International Telecommunication Union, White Paper, Sep. 2015. [Online]. Available: https://www.itu.int/rec/R-REC-M.2083-0-201509-I/en [Accessed: Nov. 29, 2018]. [4] “NGMN 5G White Paper”, Next Generation Mobile Networks, White Paper, Feb. 2015. [Online]. Available: https://www.ngmn.org/5g-white-paper/5g-white-paper.html [Accessed: Nov. 29, 2018]. [5] “5G for Connected Industries and Automation,” 5G Alliance for Connected Industries and Automation, White Paper, Nov. 2018. [Online]. Available: https://www.5g-acia.org/index.php?id=5125 [Accessed: Dec. 3, 2018]. [6] J. Wu, Z. Zhang, Y. Hong, and Y. Wen, “Cloud Radio Access Network (C-RAN): A Primer,” IEEE Network, vol. 29, no. 1, pp. 35-41, Jan.-Feb. 2015. [7] A. Checko et al., “Cloud RAN for Mobile Networks—A Technology Overview,” IEEE Communications Surveys & Tutorials, vol. 17, no. 1, pp. 405-426, First Quarter 2015. [8] “Cloud RAN and MEC: A Perfect Pairing,” European Telecommunications Standards Institute, White Paper, Feb. 2018. [Online]. Available: https://www.etsi.org/images/files/ETSIWhitePapers/etsi_wp23_MEC_and_CRAN_ed1_FINAL.pdf [Accessed: Dec. 14, 2018]. [9] N. Abbas, Y. Zhang, A. Taherkordi, and T. Skeie, “Mobile Edge Computing: A Survey,” IEEE Internet of Things Journal, vol. 5, no. 1, pp. 450-465, Feb. 2018. [10] “FG IMT-2020: Report on Standards Gap Analysis,” International Telecommunication Union, White Paper, Nov. 2015. [Online]. Available: https://www.itu.int/md/T13-SG13-151130-TD-PLEN-0208/en [Accessed: Dec. 17, 2018]. [11] J. Ordonez-Lucena, P. Ameigeiras, D. Lopez, J. J. Ramos-Munoz, J. Lorca, and J. Folgueira, “Network Slicing for 5G with SDN/NFV: Concepts, Architectures, and Challenges,” IEEE Communications Magazine, vol. 55, no. 5, pp. 80-87, May 2017. [12] “5G Empowering Vertical Industries,” 5G Infrastructure Public-Private Partnership, White Paper, Feb. 2016. [Online]. Available: https://5g-ppp.eu/wp-content/uploads/2016/02/BROCHURE_5PPP_BAT2_PL.pdf [Accessed: Dec. 22, 2018]. [13] DotEcon Ltd and Axon Partners Group. (2018). Study on Implications of 5G Deployment on Future Business Models. [Online]. Available: https://berec.europa.eu/eng/document_register/subject_matter/berec/reports/8008-study-on-implications-of-5g-deployment-on-future-business-models [Accessed: Dec. 22, 2018]. [14] X. Zhou, R. Li, T. Chen, and H. Zhang, “Network Slicing as a Service: Enabling Enterprises' Own Software-Defined Cellular Networks,” IEEE Communications Magazine, vol. 54, no. 7, pp. 146-153, July 2016. [15] X. Li et al., “Network Slicing for 5G: Challenges and Opportunities,” IEEE Internet Computing, vol. 21, no. 5, pp. 20-27, Jan. 2017. [16] “Network Functions Virtualisation (NFV); Management and Orchestration,” European Telecommunications Standards Institute, White Paper, Dec. 2014. [Online]. Available: https://www.etsi.org/deliver/etsi_gs/NFV-MAN/001_099/001/01.01.01_60/gs_NFV-MAN001v010101p.pdf [Accessed: Dec. 23, 2018]. [17] A. de la Oliva et al., “5G-TRANSFORMER: Slicing and Orchestrating Transport Networks for Industry Verticals,” IEEE Communications Magazine, vol. 56, no. 8, pp. 78-84, August 2018. [18] B. A. A. Nunes, M. Mendonca, X. Nguyen, K. Obraczka, and T. Turletti, “A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks,” IEEE Communications Surveys & Tutorials, vol. 16, no. 3, pp. 1617-1634, Third Quarter 2014. [19] Open Networking Foundation. (2014). SDN Architecture. [Online]. Available: https://www.opennetworking.org/wp-content/uploads/2013/02/TR_SDN_ARCH_1.0_06062014.pdf [Accessed: Dec. 23, 2018]. [20] Open Networking Foundation. (2016). Applying SDN Architecture to 5G Slicing. [Online]. Available: https://www.opennetworking.org/wp-content/uploads/2014/10/Applying_SDN_Architecture_to_5G_Slicing_TR-526.pdf [Accessed: Dec. 23, 2018]. [21] N. Nikaien. (2015). OpenAirlnterface Simulator/Emulator. [Online]. Available: http://www.openairinterface.org/ [Accessed: Dec. 26, 2018]. [22] X. Foukas, N. Nikaein, M. M. Kassem, M. K. Marina, and K. Kontovasilis, “FlexRAN: A Flexible and Programmable Platform for Software-Defined Radio Access Networks,” in Proc. of 12th ACM International Conference on Emerging Networking Experiments and Technologies (CoNEXT), Irvine, CA, USA, Dec. 2016, pp. 427-441. [23] S. Costanzo, I. Fajjari, N. Aitsaadi, and R. Langar, “A Network Slicing Prototype for a Flexible Cloud Radio Access Network,” in Proc. of 15th IEEE Annual Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, USA, Jan. 2018, pp. 1-4. [24] B. Sayadi et al., “SDN for 5G Mobile Networks: NORMA Perspective,” in Proc. of 11th EAI International Conference on Cognitive Radio Oriented Wireless Networks (CrownCom), Grenoble, France, May 2016, pp. 741-753. [25] R. Mijumbi, J. Serrat, J. Gorricho, N. Bouten, F. De Turck, and R. Boutaba, “Network Function Virtualization: State-of-the-Art and Research Challenges,” IEEE Communications Surveys & Tutorials, vol. 18, no. 1, pp. 236-262, First Quarter 2016. [26] M. Bagaa, T. Taleb, A. Laghrissi, A. Ksentini, and H. Flinck, “Coalitional Game for the Creation of Efficient Virtual Core Network Slices in 5G Mobile Systems,” IEEE Journal on Selected Areas in Communications, vol. 36, no. 3, pp. 469-484, March 2018. [27] F. Z. Yousaf, M. Bredel, S. Schaller, and F. Schneider, “NFV and SDN—Key Technology Enablers for 5G Networks,” IEEE Journal on Selected Areas in Communications, vol. 35, no. 11, pp. 2468-2478, Nov. 2017. [28] European Telecommunications Standards Institute (ESTI). (2016). OSM: Open-Source MANO. [Online]. Available: https://osm.etsi.org/ [Accessed: Feb. 1, 2019]. [29] L. Le, B. P. Lin, L. Tung, and D. Sinh, “SDN/NFV, Machine Learning, and Big Data Driven Network Slicing for 5G,” in Proc. of IEEE 5G World Forum (5GWF), Silicon Valley, CA, USA, July 2018, pp. 20-25. [30] H. Zhang, N. Liu, X. Chu, K. Long, A. Aghvami, and V. C. M. Leung, “Network Slicing Based 5G and Future Mobile Networks: Mobility, Resource Management, and Challenges,” IEEE Communications Magazine, vol. 55, no. 8, pp. 138-145, Aug. 2017. [31] A. N. Toosi, M. R. Mahmud, Q. chi, and R. Buyya, “Management and Orchestration of Network Slices in 5G, Fog, Edge, and Clouds: Principles and Paradigms,” in Fog and Edge Computing: Principles and Paradigms, R. Buyya and S. N. Srirama, Eds. New York: Wiley Press, 2018, pp. 79-101. [32] T. Truong-Huu, P. Murali Mohan and M. Gurusamy, “Service Chain Embedding for Diversified 5G Slices with Virtual Network Function Sharing,” IEEE Communications Letters, vol. 23, no. 5, pp. 826-829, May 2019. [33] X. Foukas, G. Patounas, A. Elmokashfi, and M. K. Marina, “Network Slicing in 5G: Survey and Challenges,” IEEE Communications Magazine, vol. 55, no. 5, pp. 94-100, May 2017. [34] I. Afolabi, T. Taleb, K. Samdanis, A. Ksentini, and H. Flinck, “Network Slicing and Softwarization: A Survey on Principles, Enabling Technologies, and Solutions,” IEEE Communications Surveys & Tutorials, vol. 20, no. 3, pp. 2429-2453, Third Quarter 2018. [35] S. Vassilaras et al., “The Algorithmic Aspects of Network Slicing,” IEEE Communications Magazine, vol. 55, no. 8, pp. 112-119, Aug. 2017. [36] W. Guan, X. Wen, L. Wang, Z. Lu, and Y. Shen, “A Service-Oriented Deployment Policy of End-to-End Network Slicing Based on Complex Network Theory,” IEEE Access, vol. 6, pp. 19691-19701, April 2018. [37] A. Kammoun, N. Tabbane, G. Diaz, A. Dandoush, and N. Achir, “End-to-End Efficient Heuristic Algorithm for 5G Network Slicing,” in Proc. of IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA), Krakow, Poland, May 2018, pp. 386-392. [38] Y. L. Lee, J. Loo, T. C. Chuah, and L. Wang, “Dynamic Network Slicing for Multitenant Heterogeneous Cloud Radio Access Networks,” IEEE Transactions on Wireless Communications, vol. 17, no. 4, pp. 2146-2161, April 2018. [39] K. T. Cheng and F. Y. Lin, “Minimax End-to-End Delay Routing and Capacity Assignment for Virtual Circuit Networks,” in Proc. of IEEE Global Communications Conference (GLOBECOM), Singapore, Singapore, Nov. 1995, pp. 2134-2138. [40] M. Leconte, G. S. Paschos, P. Mertikopoulos, and U. C. Kozat, “A Resource Allocation Framework for Network Slicing,” in Proc. of IEEE International Conference on Computer Communications (INFOCOM), Honolulu, HI, USA, April 2018, pp. 2177-2185. [41] L. Kleinrock, Queueing Systems Volume 1: Theory. New York: Wiley-Interscience, 1975. [42] M. L. Fisher, “The Lagrangian Relaxation Method for Solving Integer Programming Problems,” Management Science, vol. 50, no. 12, pp. 1861-1871, Dec. 2004. [43] A. M. Geoffrion, “Lagrangean Relaxation for Integer Programming,” in Approaches to Integer Programming, M. L. Balinski, Eds. Berlin: Springer, 1974, pp. 82-114. [44] M. L. Fisher, “An Applications Oriented Guide to Lagrangian Relaxation,” Interfaces, vol. 15, no. 2, pp. 10-21, April 1985. [45] 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. [46] M. Held and R. M. Karp, “The Traveling-Salesman Problem and Minimum Spanning Trees: Part II,” Mathematical Programming: Series A and B, vol. 1, no. 1, pp. 6-25, Dec. 1971. [47] M. Held, P. Wolfe, and H. P. Crowder, “Validation of Subgradient Optimization,” Mathematical Programming, vol. 6, no. 1, pp. 62-88, Dec. 1974. [48] G. E. Moore, “Cramming More Components onto Integrated Circuits,” Electronics, vol. 86, no. 1, pp. 114-117, April 1965. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/7237 | - |
| dc.description.abstract | 網路切片自提出便被視為第五代行動通訊網路(5G)的關鍵技術，預期能實 現 5G 時代多樣化的應用需求和垂直產業。建基於集中式無線接取網路、軟體定義 網路和網路功能虛擬化等技術上的突破，網路切片將實體網路虛擬邏輯化，進而劃 分成不同服務的可行性已被證實，是一個更具效率、彈性及可靠性的架構。
然而，由於缺乏有效且全面性的資源分配機制，要達成網路協作仍存在挑戰。 本篇研究便以此為出發點，提出一個站在網路協作者角度的傳遞路徑與運算資源 管理情境，以期能動態地切割與配置端對端獨立網路切片去滿足企業的垂直需求。 而此複雜的問題更進一步被我們設計成數學模型，目標為最大化整體收益。我 們利用拉格朗日鬆弛法來解決此模型，並且發展一個以拉格朗日鬆弛法為基礎的 啟發式演算法來求得可行解。最後，透過一系列包含多元需求以及不同實體網路建 置環境的實驗，此演算法也被證明具有最佳化資源利用的能力。 | zh_TW |
| dc.description.abstract | Network slicing is viewed as an emerging paradigm for satisfying diverse applications and vertical industries which are 5G network anticipated to empower. Based on architectural breakthroughs such as C-RAN, SDN, and NFV, the concept offering network slices with independent control as services over a common physical infrastructure is proved to be practicable and able to better make use of resources.
However, challenges remain in achieving network orchestration due to the lack of a comprehensive resource management approach. Therefore, a traffic path and computing power assignment problem of network slicing from an orchestrator viewpoint is presented in this thesis. The objective of the orchestrator is to dynamically allocate resources and gain maximum rewards by satisfying E2E slicing requests of vertical companies. The complex problem is further formulated to a mathematical model and optimally solved by adopting Lagrangian relaxation method. Moreover, a Lagrangian relaxation- based approach with the Drop-and-Add algorithm is proposed for fulfilling E2E slices and get optimal feasible solutions. At last, the developed solution approach is validated by computational experiments to be effective to manage resources when facing diverging QoS requirements and different network infrastructure. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-19T17:40:28Z (GMT). No. of bitstreams: 1 ntu-108-R06725016-1.pdf: 5485236 bytes, checksum: cfdd6845ef9908ae01867e9a85a2a687 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vii LIST OF TABLES viii LIST OF ABBREVIATIONS x Chapter 1 Introduction 1 1.1 Background 1 1.2 Motivation 6 1.3 Thesis Organization 7 Chapter 2 Literature Review 8 2.1 Foundations of Network Slicing: SDN and NFV 8 2.2 The Architecture, Business Model and Challenges of Network Slicing 12 2.3 Resource Management Issues in Network Slicing 15 2.4 Summary of Literature Review 17 Chapter 3 Problem Formulation 19 3.1 Problem Description 19 3.2 Mathematical Formulation 23 3.2.1 Primal Problem 1 25 3.2.1.1 Objective Function 27 3.2.1.2 Path Assignment Constraints 27 3.2.1.3 Slice Assignment Constraints 27 3.2.1.4 Capacity Constraints 27 3.2.1.5 Delay Constraints 28 3.2.2 Primal Problem 2 29 3.2.2.1 Path Assignment Constraints 32 3.2.2.2 Slice Assignment Constraints 32 3.2.2.3 Capacity Constraints 32 3.2.2.4 Delay Constraints 32 Chapter 4 Solution Approach 33 4.1 The Lagrangian Relaxation Method 33 4.2 Solution Approach for the Primal Problem 35 4.2.1 The Lagrangian Relaxation Problem 35 4.2.1.1 Subproblem 1 (related to decision variable xp) 38 4.2.1.2 Subproblem 2 (related to decision variable ysn) 40 4.2.1.3 Subproblem 3 (related to decision variable zs) 42 4.2.1.4 Subproblem 4 (related to decision variable vsn and jn) 43 4.2.1.5 Subproblem 5 (related to decision variable wsl and kl) 47 4.2.2 The Dual Problem and the Subgradient Method 49 4.2.3 Getting Primal Feasible Solution 52 4.2.4 Summary of Solution Approach 56 Chapter 5 Computational Experiments 59 5.1 Experiment Environment 59 5.2 Performance Metrics 65 5.2.1 Gap 65 5.2.2 Improvement Rate 65 5.3 Experiment Scenarios and Results 66 5.3.1 Static Network with Increasing Demands 66 5.3.2 Static Network with Increasing Capacity 71 5.3.3 Static Network with Increasing Density of Demands 75 5.3.4 Decreasing Ratio between Number of Edge Clouds and Core Clouds 78 5.4 Discussion of Experiment Results 81 Chapter 6 Conclusions and Future Work 82 6.1 Conclusions 82 6.2 Future Work 83 6.2.1 Resource Sharing between Slices 83 6.2.2 Pricing Policies of Network Operators 83 ACKNOWLEDGMENT 84 REFERENCES 85 | |
| dc.language.iso | en | |
| dc.title | 第五代行動通訊切片式網路協作與資源管理機制最佳化 | zh_TW |
| dc.title | Slicing Network Function Orchestration and Resource Management Optimization in 5G C-RANs | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 溫演福(Yean-Fu Wen),莊東穎(Tong-Ying Juang),李漢銘(Hahn-Ming Lee),黃彥男(Yen-Nun Huang) | |
| dc.subject.keyword | 第五代移動通訊系統,網路切片,網路協作,集中式無線接取網路,垂直產業,資源管理,服務品質,拉格朗日鬆弛法, | zh_TW |
| dc.subject.keyword | 5G,Network Slicing,Network Orchestration,Cloud Radio Access Network (C-RAN),Vertical Industry,Resource Management,Quality of Service (QoS),Lagrangian Relaxation, | en |
| dc.relation.page | 91 | |
| dc.identifier.doi | 10.6342/NTU201902743 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2019-08-07 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| dc.date.embargo-lift | 2029-08-07 | - |
| Appears in Collections: | 資訊管理學系 | |
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| File | Size | Format | |
|---|---|---|---|
| ntu-108-1.pdf Until 2029-08-07 | 5.36 MB | Adobe PDF |
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