面向未來5G服務按需應用的邊緣網路任務排程與虛擬化服務佈署策略

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：59

、訪客IP：3.131.13.24

姓名

曾家偉(Chia-Wei Tseng) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

面向未來5G服務按需應用的邊緣網路任務排程與虛擬化服務佈署策略
(Edge Network Task Scheduling and NFV Deployment Strategies Toward Future 5G Service On-Demand Applications)

相關論文

★ 無線行動隨意網路上穩定品質服務路由機制之研究	★ 應用多重移動式代理人之網路管理系統
★ 應用移動式代理人之網路協同防衛系統	★ 鏈路狀態資訊不確定下QoS路由之研究
★ 以訊務觀察法改善光突發交換技術之路徑建立效能	★ 感測網路與競局理論應用於舒適性空調之研究
★ 以搜尋樹為基礎之無線感測網路繞徑演算法	★ 基於無線感測網路之行動裝置輕型定位系統
★ 多媒體導覽玩具車	★ 以Smart Floor為基礎之導覽玩具車
★ 行動社群網路服務管理系統－應用於發展遲緩兒家庭	★ 具位置感知之穿戴式行動廣告系統
★ 調適性車載廣播	★ 車載網路上具預警能力之車輛碰撞避免機制
★ 應用於無線車載網路上之合作式交通資訊傳播機制以改善車輛擁塞	★ 智慧都市中應用車載網路以改善壅塞之調適性虛擬交通號誌

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 ( 永不開放)

摘要(中)

行動、雲端與物聯網的快速發展，帶動網路資源分配、訊務處理和服務管理的需求，驅使傳統網路基礎架構轉型。軟體定義網路（Software Defined Network, SDN）以及網路功能虛擬化（Network Functions Virtualization, NFV）技術的出現，將現今複雜的網路架構轉變成虛擬、可程式化的架構，不僅帶動ICT產業的變革，也催生了邊緣運算（Edge Computing）的興起，引領新一波的5G科技的發展浪潮。
如何因應不同服務需求，快速分配虛擬化運算資源，進一步提供按需服務（On-demand Service）的應用是未來5G 物聯網服務發展的關鍵之一。為減少資料往返雲端的等待時間及降低網路頻寬成本，本研究提出以閘道器（Gateway）為主的邊緣運算(Edge Computing)服務運作模式，藉由調整Edge Gateway的任務排程，可以較少的等待時間處理更多的服務需求，讓用戶的服務需求可儘量就近在邊緣網路的Gateway裝置上進行處理，如有超出edge gateway的運算能力或無法處理的服務需求，再轉給雲端處理。在VNF服務佈署方面，將NFV虛擬化技術應用於快速部署以及SDN / OpenFlow流量控制可以提高網路服務部署的靈活性和可擴展性。為了實現NFV的快速佈署，本論文分析了幾種不同的佈署策略，探討可能影響VNF佈署效率的因素。此外，本研究也比較VM以及Docker輕量化虛擬技術的差異，以因應邊緣運算裝置資源配置的需求。在邊緣運算應用方面，由於網路安全一直是資通訊領域研究的重要領域，本研究整合邊緣運算與SDN/NFV網路技術，利用SFC服務功能鏈建立可彈性配置之資安服務按需系統Service On-Demand (SOD)，可提升網路資安服務的應用效率與降低硬體設備成本投入，並提供滿足不同使用者需求的創新行動邊緣網路資安應用與服務模式。
本研究所提出的邊緣運算服務架構，有助於降低傳統雲端架構的運算負荷、提升邊緣運算裝置的運作效率，可作為未來5G實現雲霧運算（Cloudy-Fog Computing）整合創新應用的發展基礎。

摘要(英)

With the rapid development of mobile, cloud and Internet of Things (IoT), the demand for network resource allocation, traffic processing and service management drives the transformation of traditional network infrastructure. The emergence of Software Defined Network (SDN) and Network Functions Virtualization (NFV) technology turns the complicated network architecture into a virtual and programmable network. SDN/NFV not only drives the transformation of the Information and Communication Technology (ICT) industry, but also the rise of edge computing, leading the development trend of 5G technology in the future.
How to meet the requirements of different users, flexible and rapid allocation of virtual computing resources, and further provide on-demand service is the key to the future development of 5G IoT services. In order to reduce the waiting time of data to and from the cloud and reduce the network bandwidth cost, this paper proposes a gateway-based edge computing service model. By adjusting the edge gateway′s task schedule, more service requests can be processed with less waiting time. The user′s service requests can be processed as close as possible to the edge network devices. If the computing power required by the service exceeds the computing power of the edge gateway or cannot be processed, it will be forwarded to the cloud for processing. In terms of Virtual Network Function (VNF) deployment, the application of NFV virtualization technology and SDN OpenFlow traffic control mechanism can significantly improve the flexibility and scalability of network service deployment. In order to achieve rapid deployment of NFV, this paper analyzes several different deployment strategies and explores factors that may affect the efficiency of VNF deployment. In addition, this paper also compares the differences between Virtual Machine (VM) and Docker virtualization technologies to meet the requirements of edge computing device resource allocation. In terms of edge computing applications, because network security is an important research direction of 5G, the paper utilizes Service Function Chaining (SFC) technology to design and implementation of a Service On-Demand (SOD) system for security applications. SFC can improve the application efficiency of network security services and reduce the cost of hardware equipment and provide innovative action edge network security application and service models that can meet the needs of different users.
The edge computing service architecture proposed in this paper helps to reduce the computational load of traditional cloud architecture and improve the operational efficiency of edge computing devices. It can be used as the basis for the development of Cloudy-Fog Computing integrated security applications in the future 5G network.

關鍵字(中)

★ 邊緣運算
★ 任務排程
★ 快速佈署
★ 按需服務
★ 網路功能虛擬化

關鍵字(英)

★ Edge Computing
★ Task Scheduling
★ Rapid Deployment
★ Service On-Demand
★ Network Functions Virtualization

論文目次

摘要 i
Abstract ii
聲明 iv
致謝 v
Contents vi
List of Figures ix
List of Tables xi
Abbreviation xii
Explanation of Notations xiv
Chapter 1. Introduction 1
1.1 Overview 1
1.2 Motivations and Goals 5
1.3 Contributions 7
1.4 Dissertation Organization 8
Chapter 2. Background and Related Works 9
2.1 Edge Computing and Task Scheduling 9
2.2 Network Function Virtualization and VNF Deployment 13
2.3 Software Defined Network and Service Function Chain 18
Chapter 3. Gateway-Based Edge Computing Service Architecture 24
3.1 Network Functions Scheduling Analysis 24
A. Sequential Service Model Analysis 27
B. Parallel Service Model Analysis 29
3.2 Gateway-Based Edge Computing Architecture 31
A. Resource Estimation 33
B. Task Scheduling 34
C. Lightweight VNF Service Configuration 38
Chapter 4. NFV Deployment Strategies for Edge Computing 40
4.1 Overview the NFV Deployment Strategies 40
4.2 NFV Deployment Strategies for VNF Resource allocation in SDN Network 42
A. Sequential clone by one disk 43
B. Parallel clone by one disk 44
C. Branching clone by one disk 45
D. Branching clone by four disks 46
E. One-Transmission-One-Reception 47
F. One-Transmission-More-Reception 47
Chapter 5. Service On-demand System in Edge Network 50
5.1 SFC Service Mapping and Operation in Edge Network 50
A. Service Request and VNF mapping Model 51
B. Service On-Demand System Operations 55
5.2 Design and Implementation of a SOD System 58
A. SOD System Framework Design 61
B. Flow Rule Conversion Algorithms 65
Chapter 6. Experimental Results 69
6.1 Edge Computing and Cloud Computing Comparison 69
6.2 Task Scheduling Simulation for Edge Computing 74
6.3 VNFs Deployment Strategies for Edge Computing 80
A. Full Clone Deployment Scenario 81
B. Linked Clone Deployment Scenario 86
6.4 Comparing VM versus Docker deployment 90
6.5 Service Function Performance Evaluation 95
Chapter 7. Conclusions and Future Works 98
7.1 Conclusions 98
7.2 Future Works 100
References 101
Publication List 111

參考文獻

[1] L. Ma, X. Wen, L. Wang, Z. Lu, and R. Knopp, “An SDN/NFV based framework for management and deployment of service based 5G core network,” in China Communications, vol. 15, no. 10, pp. 86-98, Oct. 2018. doi: 10.1109/CC.2018.8485472
[2] Q. Duan, N. Ansari, and M. Toy, “Software-defined network virtualization: an architectural framework for integrating SDN and NFV for service provisioning in future networks,” in IEEE Network, vol. 30, no. 5, pp. 10-16, Sep. 2016. doi: 10.1109/MNET.2016.7579021
[3] ETSI GS NFV 002, “Network functions virtualization (NFV); architectural framework v1.2.1,” ETSI, Group Specification, October 2014. [Online]. Available: https://docbox.etsi.org/ISG/NFV/Open/Publications_pdf/Specs-Reports
[4] ONF, “SDN Architecture,” June 2014. [Online]. Available : www.opennetworking.org/images/stories/downloads/sdn-resources/technical-reports/TR_SDN_ARCH_1.0_06062014.pdf
[5] R. Muñoz, Ricard Vilalta, Noboru Yoshikane, Ramon Casellas, Ricardo Martinez, Takehiro Tsuritani and Itsuro, “Integration of IoT, Transport SDN, and Edge/Cloud Computing for Dynamic Distribution of IoT Analytics and Efficient Use of Network Resources,” in Journal of Lightwave Technology, vol. 36, no. 7, pp. 1420-1428, 1 Apr. 2018. doi: 10.1109/JLT.2018.2800660
[6] M. T. Kakiz, E. Öztürk, and T. Çavdar, “A novel SDN-based IoT architecture for big data,” 2017 International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, 2017, pp. 1-5.
[7] S. Schriegel, T. Kobzan and J. Jasperneite, “Investigation on a distributed SDN control plane architecture for heterogeneous time sensitive networks,” 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS), Imperia, pp. 1-10, 2018.
[8] N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford, S. Shenker, and J. Turner, “OpenFlow”, SIGCOMM Comput. Commun. Rev., vol. 38, no. 2, p. 69, 2008.
[9] L. Ma, X. Wen, L. Wang, Z. Lu and R. Knopp, “An SDN/NFV based framework for management and deployment of service based 5G core network,” in China Communications, vol. 15, no. 10, pp. 86-98, Oct. 2018. doi: 10.1109/CC.2018.8485472
[10] F. Z. Yousaf, M. Bredel, S. Schaller, and F. Schneider, “NFV and SDN—Key Technology Enablers for 5G Networks,” in IEEE Journal on Selected Areas in Communications, vol. 35, no. 11, pp. 2468-2478, Nov. 2017. doi: 10.1109/JSAC.2017.2760418
[11] Source Packet Routing in Networking (spring), [Online]. Available: https://datatracker.ietf.org/group/spring/about/
[12] Service Function Chaining (sfc). [Online]. Available: https://datatracker.ietf.org/wg/sfc/documents/
[13] A. C. Baktir, A. Ozgovde, and C. Ersoy, “How Can Edge Computing Benefit From Software-Defined Networking: A Survey, Use Cases, and Future Directions,” in IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2359-2391, Fourthquarter 2017. doi: 10.1109/COMST.2017.2717482
[14] C.-W. Tseng, Y.-K. Huang, F.-H. Tseng, Y.-T. Yang, C.-C. Liu, and L.-D. Chou, “Micro Operator Design Pattern in 5G SDN/NFV Network,” Wireless Communications and Mobile Computing (WCMC), vol. 2018, July 2018. https://doi.org/10.1155/2018/3471610
[15] M. Gharbaoui, C. Contoli, G. Davoli, G. Cuffaro, B. Martini, F. Paganelli, W. Cerroni, P. Cappanera, and P. Castoldi, “Demonstration of Latency-Aware and Self-Adaptive Service Chaining in 5G/SDN/NFV infrastructures,” 2018 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), Verona, Italy, pp. 1-2, 2018. doi: 10.1109/NFV-SDN.2018.8725645
[16] W. Yu, F. Liang, X. He, W. Hatcher, C. Lu, J. Lin, and X. Yang, “A Survey on the Edge Computing for the Internet of Things,” in IEEE Access, vol. 6, pp. 6900-6919, 2018. doi: 10.1109/ACCESS.2017.2778504
[17] P. Mach and Z. Becvar, “ Mobile Edge Computing: A Survey on Architecture and Computation Offloading,” in IEEE Communications Surveys & Tutorials, Volume: 19, Issue: 3, pp.1628-1656, 2017. doi: 10.1109/COMST.2017.2682318
[18] N. Abbas, Y. Zhang, A. Taherkordi, and T. Skeie, “ Mobile Edge Computing: A Survey,” in IEEE Internet of Things Journal, vol. 5, Issue: 1, pp.450-465, 2018. doi: 10.1109/JIOT.2017.2750180
[19] C. -W. Tseng, F. -H. Tseng, Y. -T. Yang, C. -C. Liu, and L. -D. Chou, “Task Scheduling for Edge Computing with Agile VNFs On-Demand Service Model toward 5G and Beyond,” Wireless Communications and Mobile Computing (WCMC), vol. 2018, July 2018. https://doi.org/10.1155/2018/7802797
[20] H. Zhu and C. Iluang, “VNF-B&B: Enabling edge-based NFV with CPE resource sharing,” 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Montreal, QC, pp. 1-5, 2017. doi: 10.1109/PIMRC.2017.8292421
[21] M. Benisha, R. T. Prabu, and V. T. Bai, “Requirements and challenges of 5G cellular systems,” 2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), Chennai, pp. 251-254, 2016. doi: 10.1109/AEEICB.2016.7538283
[22] K. Sienkiewicz, W. Latoszek, and P. Krawiec, “Services orchestration within 5G networks — Challenges and solutions,” 2018 Baltic URSI Symposium (URSI), Poznan, pp. 265-268, 2018. doi: 10.23919/URSI.2018.8406739
[23] C. -W. Tseng, P. -H. Lai, B. -S. Huang, L. -D. Chou, and M. -C. Wu, “NFV deployment strategies in SDN network,” International Journal of High Performance Computing and Networking (IJHPCN), vol. 14 no. 2, pp. 237-248, 2019. doi: 10.1504/IJHPCN.2019.10022739
[24] I. Ahmad, T. Kumar, M. Liyanage, J. Okwuibe, M. Ylianttila, and A. Gurtov, “5G security: Analysis of threats and solutions,” 2017 IEEE Conference on Standards for Communications and Networking (CSCN), Helsinki, pp. 193-199, 2017. doi: 10.1109/CSCN.2017.8088621
[25] C. Martín Fernández, M. Díaz Rodríguez, and B. Rubio Muñoz, “An Edge Computing Architecture in the Internet of Things,” 2018 IEEE 21st International Symposium on Real-Time Distributed Computing (ISORC), Singapore, pp. 99-102, 2018. doi: 10.1109/ISORC.2018.00021
[26] L. Zhao, W. Sun, Y. Shi, and J. Liu, “Optimal Placement of Cloudlets for Access Delay Minimization in SDN-Based Internet of Things Networks,” in IEEE Internet of Things Journal, vol. 5, no. 2, pp. 1334-1344, Apr. 2018. doi: 10.1109/JIOT.2018.2811808
[27] S. Wang, X. Zhang, Y. Zhang, L. Wang, J. Yang, and W. Wang, “A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications,” in IEEE Access, vol. 5, pp. 6757-6779, 2017.doi: 10.1109/ACCESS.2017.2685434
[28] Y. Liu, J. E. Fieldsend, and G. Min, “A Framework of Fog Computing: Architecture, Challenges, and Optimization,” in IEEE Access, vol. 5, pp. 25445-25454, 2017. doi: 10.1109/ACCESS.2017.2766923
[29] ETSI Multi-access Edge Computing, [Online]. Available: http://www.etsi.org/technologies-clusters/ technologies/multi-access-edge-computing
[30] OpenFog Consortium, [Online]. Available : https://www.openfogconsortium.org/
[31] Y. Mao, C. You, J. Zhang, K. Huang, and K. B. Letaief, “A Survey on Mobile Edge Computing: The Communication Perspective,” in IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2322-2358, Fourthquarter 2017.doi: 10.1109/COMST.2017.2745201
[32] Cisco, The Internet of Things: How the Next Evolution of the Internet Is Changing Everything white paper, [Online]. Available : https://www.cisco.com/c/dam/en_us/.../IoT_IBSG_0411FINAL.pdf
[33] IDC, FutureScape: Worldwide Internet of Things 2017 Predictions, November 2016, [Online]. Available : https://www.idc.com/getdoc.jsp?containerId=US41910716
[34] Y. Guo, H. Zhu, and L. Yang, “Service-oriented network virtualization architecture for Internet of Things,” in China Communications, vol. 13, no. 9, pp. 163-172, Sept. 2016. doi: 10.1109/CC.2016.7582308
[35] N. Bizanis and F. A. Kuipers, “SDN and Virtualization Solutions for the Internet of Things: A Survey,” in IEEE Access, vol. 4, pp. 5591-5606, 2016. doi: 10.1109/ACCESS.2016.2607786
[36] T. Lin, B. Park, H. Bannazadeh, and A. Leon-Garcia, “Demo Abstract: End-to-End Orchestration across SDI Smart Edges,” 2016 IEEE/ACM Symposium on Edge Computing (SEC), 2016. doi: 10.1109/SEC.2016.42
[37] A. Amjad, F. Rabby, S. Sadia, M. Patwary, and E. Benkhelifa, “Cognitive Edge Computing based resource allocation framework for Internet of Things,” 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC), Valencia, pp. 194-200, 2017. doi: 10.1109/FMEC.2017.7946430
[38] N. Abbas, Y. Zhang, A. Taherkordi, and T. Skeie,”Mobile Edge Computing: A Survey,” IEEE Internet of Thing sJournal, vol. 5, no.1, pp. 450-465, Feb. 2018. doi: 10.1109/JIOT.2017.2750180
[39] C. Fan, H. Deng, F. Wang, S. Wei, W. Dai, and B. Liang, “A Survey on Task Scheduling Method in Heterogeneous Computing System,” 2015 8th International Conference on Intelligent Networks and Intelligent Systems (ICINIS), Tianjin, pp. 90-93, 2015. doi: 10.1109/ICINIS.2015.42
[40] P. Akilandeswari and H. Srimathi,”Survey and Analysis on Task Scheduling in Cloud Environment,” Indian Journal of Science and Technology, vol. 9, issue. 37, Oct. 2016. doi: 10.17485/ijst/2016/v9i37/102058
[41] E. Meriam and N. Tabbane, “A Survey on Cloud Computing Scheduling Algorithms,” 2016 Global Summit on Computer & Information Technology (GSCIT), Sousse, 2016, pp. 42-47. doi: 10.1109/GSCIT.2016.6
[42] H. Wang, J. Gong, Y. Zhuang, H. Shen, and J. Lach, “Healthedge: Task Scheduling for Edge Computing with Health Emergency and Human Behavior Consideration in Smart Homes,” 2017 International Conference on Networking, Architecture, and Storage (NAS), Shenzhen, 2017. doi: 10.1109/NAS.2017.8026861
[43] J. Liu, Y. Mao, J. Zhang and K. B. Letaief, “Delay-optimal computation task scheduling for mobile-edge computing systems,” 2016 IEEE International Symposium on Information Theory (ISIT), Barcelona, pp. 1451-1455, 2016. doi: 10.1109/ISIT.2016.7541539
[44] R. Mijumbi, J. Serrat, J. L. Gorricho, N. Bouten, F. De Turck, and S. Davy, “Design and evaluation of algorithms for mapping and scheduling of virtual network functions,” Proceedings of the 2015 1st IEEE Conference on Network Softwarization (NetSoft), London, pp. 1-9, 2015. doi: 10.1109/NETSOFT.2015.7116120
[45] P. Samal and P. Mishra,”Analysis of variants in Round Robin Algorithms for load balancing in Cloud Computing”, International Journal of Computer Science and Information Technologies, vol. 4(3), pp. 416-419, 2013.
[46] L. Ma, X. Wen, L. Wang, Z. Lu and R. Knopp, “An SDN/NFV based framework for management and deployment of service based 5G core network,” in China Communications, vol. 15, no. 10, pp. 86-98, Oct. 2018. doi: 10.1109/CC.2018.8485472
[47] F. Alvarez, D. Breitgand, D. Griffin, P. Andriani, S. Rizou, N. Zioulis, F. Moscatelli, J. Serrano, M. Keltsch, P. Trakadas, T. Johoa Phan, A. Weit, U. Acar, O. Prieto, F. Landanza, G. Carrozzo, H. Koumaras, D. Zarpalas, and D. Jimenez, “An Edge-to-Cloud Virtualized Multimedia Service Platform for 5G Networks," in IEEE Transactions on Broadcasting, vol. 65, no. 2, pp. 369-380, June 2019. doi: 10.1109/TBC.2019.2901400
[48] N. Jain and S. Choudhary, “Overview of virtualization in cloud computing,” 2016 Symposium on Colossal Data Analysis and Networking (CDAN), Indore, pp. 1-4, 2016. doi: 10.1109/CDAN.2016.7570950
[49] X. Jia and L. Heng, “Virtualization in Enterprises′ Different Growth Stages and Its Motives: A Classical Grounded Theory Research,” 2014 Seventh International Joint Conference on Computational Sciences and Optimization, Beijing, pp. 228-232, 2014. doi: 10.1109/CSO.2014.49
[50] T. Salah, M. J. Zemerly, C. Y. Yeun, M. Al-Qutayri, and Y. Al-Hammadi, “Performance comparison between container-based and VM-based services,” 2017 20th Conference on Innovations in Clouds, Internet and Networks (ICIN), Paris, pp. 185-190, 2017. doi: 10.1109/ICIN.2017.7899408
[51] Wikipedia, Hypervisor, [Online] https://en.wikipedia.org/wiki/Hypervisor
[52] Xen, [Online]. Available: https://www.xenproject.org/
[53] VMware, [Online]. Available: http://www.vmware.com/tw.html
[54] KVM, [Online]. Available: http://www.linux-kvm.org/
[55] VirtualBox, [Online]. Available: https://www.virtualbox.org/
[56] H. Lauer and N. Kuntze, “Hypervisor-Based Attestation of Virtual Environments,” 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress, pp.333-340, 2016. doi: 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0067
[57] L. -D. Chou, C. -W. Tseng, P. -H. Lai, S. -Y. Hsieh, and M. -C. Wu, “SDN/NFV Virtualization Testbed with Automatic Deployment and Management Functions,” Proceedings of The Second International Conference on Electronics and Software Science (ICESS2016), Takamatsu, Japan, pp. 112-121, Nov. 2016,.
[58] M. V. Malik and C. Barde, “Survey on architecture of leading hypervisors and their live migration techniques”, International journal of computer science and mobile computing, vol. 3, no. 11, pp. 65-72, 2014.
[59] A. Blenk, A. Basta, M. Reisslein, and W. Kellerer, “Survey on Network Virtualization Hypervisors for Software Defined Networking,” in IEEE Communications Surveys & Tutorials, vol. 18, no. 1, pp. 655-685, Firstquarter 2016. doi: 10.1109/COMST.2015.2489183
[60] J. Hwang, S. Zeng, F. y. Wu, and T. Wood, “A Component-Based Performance Comparison of Four Hypervisors,” 2013 IFIP/IEEE International Symposium on Integrated Network Management, Ghent, Belgium, pp. 269-276, 2013.
[61] Docker Hub,[Online]. Available: https://hub.docker.com/
[62] C. -W. Tseng, M. -S. Tsai, Y. -T. Yang, and L. -D. Chou, “A Rapid Auto-Scaling Mechanism in Cloud Computing Environment”, The 13th Int′l Conf on Grid, Cloud, and Cluster Computing , Las Vegas, Nevada, USA, pp. 31-34, July. 2017.
[63] D. Luong, H. Thieu, A. Outtagarts, and B. Mongazon-Cazavet, “Telecom microservices orchestration,” 2017 IEEE Conference on Network Softwarization (NetSoft), Bologna, pp. 1-2, 2017. doi: 10.1109/NETSOFT.2017.8004255
[64] GitHub.Inc, [Online]. Available: https://github.com/
[65] B. I. Ismail, E. M. Goortani, M. B. A. Karim, W. M. Tat, S. Setapa, J. Y. Luke, and O. H. Hoe, “Evaluation of Docker as Edge computing platform,” 2015 IEEE Conference on Open Systems (ICOS), Melaka, pp. 130-135. 2015. doi: 10.1109/ICOS.2015.7377291
[66] R. Morabito and N. Beijar, “Enabling Data Processing at the Network Edge through Lightweight Virtualization Technologies,” 2016 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops), London, pp. 1-6. 2016. doi: 10.1109/SECONW.2016.7746807
[67] X. Li and C. Qian, “The virtual network function placement problem,” in Proc. IEEE Conf. Comput. Commun. Workshops (INFOCOM WKSHPS), Hong Kong, China, pp. 69-70, 2015. doi: 10.1109/INFCOMW.2015.7179347
[68] M. Ghaznavi, A. Khan, N. Shahriar, K. Alsubhi, R. Ahmed, and R. Boutaba, “Elastic virtual network function placement,” in Proc. IEEE CloudNet, Niagara Falls, ON, Canada, pp. 255-260, 2015. doi: 10.1109/CloudNet.2015.7335318
[69] A. Sun, T. Ji, and J. Wang, “Cloud platform scheduling strategy based on virtual machine resource behaviour analysis,” International Journal of High Performance Computing and Networking (IJHPCN), vol. 9, no. 1/2, pp. 61-69, 2016. doi: 10.1504/IJHPCN.2016.074659
[70] K. Li, H. Zheng, and J. Wu, “Migration-based virtual machine Placement in Cloud Systems,” IEEE 2nd International Conference on Cloud Networking(CloudNet), San Francisco, CA, USA, pp. 83-90, 2013. doi: 10.1109/CloudNet.2013.6710561
[71] Z. Usmani and S. Singh, “A Survey of Virtual Machine Placement Techniques in a Cloud Data Center,” Procedia Computer Science, vol. 78, pp. 491-498, 2016. doi: 10.1016/j.procs.2016.02.093
[72] H. Moens and F. D. Turck, “VNF-P : A Model for Efﬁcient Placement of Virtualized Network Functions,” in International Conference on Network and Service Management (CNSM), Rio de Janeiro, Brazil, pp. 418-423, 2014. doi: 10.1109/CNSM.2014.7014205
[73] A. Mohammadkhan, S. Ghapani, G. Liu, W, Zhang, K. K. Ramakrishnan, and T. Wood, “Virtual function placement and traffic steering in fexible and dynamic software deﬁned networks,” in Proc. IEEE Int. Workshop Local Metropolitan Area Netw. (LANMAN), Beijing, China, pp. 1-6, Apr. 2015. doi: 10.1109/LANMAN.2015.7114738
[74] R. Cohen, L. Lewin-Eytan, J. S. Naor, and D. Raz, “Near optimal placement of virtual network functions,” 2015 IEEE Conference on Computer Communications (INFOCOM), Kowloon, Hung Kong, China, pp. 1346–1354, 2015. doi: 10.1109/INFOCOM.2015.7218511
[75] R. Mijumbi, J. Serrat, J. Gorricho, N. Bouten, F. D. Turck, and S. Davy, “Design and evaluation of algorithms for mapping and scheduling of virtual network functions,” in Proceedings of the 1st IEEE Conference on Network Softwarization (NetSoft 2015), London, United Kingdom, pp. 1-9, 2015. doi: 10.1109/NETSOFT.2015.7116120
[76] W. Rankothge, J. Ma, F. Le, A. Russo and J. Lobo, “Towards making network function virtualization a cloud computing service,” 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), Ottawa, ON, pp. 89-97, 2015. doi: 10.1109/INM.2015.7140280
[77] S. Kaur and V. Pandey, “A Survey on Virtual Machine Migration Techniques In Cloud Computing,” Computer Engineering and Intelligent Systems, vol. 6, no. 7, 2015.
[78] J. Sekhar and G. Jeba, “Energy Efficient VM Live Migration in Cloud Data Centers’, International Journal of Computer Science and Network (IJCSN), vol. 2, issue. 2, pp. 71-75, 2013.
[79] U. Sharma, P. Shenoy, S. Sahu, and A. Shaikh, “A cost-aware elasticity provisioning system for the cloud,” Proceedings of the 2011 31st International Conference on Distributed Computing Systems (ICDCS), Washington, DC, USA , pp. 559-570, 2011. doi: 10.1109/ICDCS.2011.59
[80] S. Clayman, E. Maini, A. Galis, A. Manzalini, and N. Mazzocca, “The dynamic placement of virtual network functions,” in IEEE Network Operations and Management Symposium (NOMS), Krakow, Poland, pp. 1-9, 2014. doi: 10.1109/NOMS.2014.6838412
[81] OpenFlow, [online]. Available: http://archive.openflow.org/
[82] A. Lara, A. Kolasani and B. Ramamurthy, “Network Innovation using OpenFlow: A Survey,” Communications Surveys & Tutorials, IEEE, vol. 16, no. 1, pp. 493-512, 2014. doi: 10.1109/SURV.2013.081313.00105
[83] ONF, “SDN architecture Overview,” Open Networking Foundation, 2013. [Online]. Available: https://www.opennetworking.org/images/stories/downloads/sdn-resources/technical-reports/TR_SDN-ARCH-Overview-1.1-11112014.02.pdf
[84] RYU, [Online]. Available:https://osrg.github.io/ryu/
[85] ONOS, “ONOS - A new carrier-grade SDN network operating system designed for high availability, performance, scale-out,” [Online]. Available: http://onosproject.org/.
[86] OpenDaylight, “OpenDaylight: A Linux Foundation Collaborative Project,” [Online]. Available: http://www.opendaylight.org.
[87] ONF, OpenFlow switch specification, 2013, [Online]. Available: https://www.opennetworking.org/sdn-resources/onf-specifications
[88] ONF, OF-Config, OpenFlow management and configuration protocol 2013, [Online]. Available: https://www.opennetworking.org/sdn-resources/onf-specifications/openflow-config
[89] Openstack, [Online]. Available: https://www.openstack.org/
[90] ITU-T,”Framework of software-defined networking,” ITU-T, Tech. Rep., June 2014, recommendation ITU-T Y.3300. [Online]. Available: http://www.itu.int/rec/T-REC-Y.3300-201406-I/en
[91] ETSI GS NFV 002, “Network functions virtualization (NFV); architectural framework v1.1.1,” ETSI, Tech. Rep., October 2013. [Online]. Available: http://www.etsi.org/deliver/etsi gs/NFV/001 099/ 002/01.01.01 60/gs NFV002v010101p.pdf
[92] IETF, Software Defined Networking (sdnrg), [Online]. Available: https://www.ietf.org/proceedings/82/sdn.html
[93] OpenDaylight, “OpenDaylight: A Linux Foundation Collaborative Project,” [Online]. Available: http://www.opendaylight.org
[94] F. A. Lopes, M. Santos, R. Fidalgo, and S. Fernandes, “A Software Engineering Perspective on SDN Programmability,” in IEEE Communications Surveys & Tutorials, vol. 18, no. 2, pp. 1255-1272, Secondquarter 2016. doi: 10.1109/COMST.2015.2501026
[95] C. Sieber, A. Basta, A. Blenk, and W. Kellerer, “Online resource mapping for SDN network hypervisors using machine learning,” 2016 IEEE NetSoft Conference and Workshops (NetSoft), Seoul, pp. 78-82, 2016. doi: 10.1109/NETSOFT.2016.7502447
[96] Y. Fu, Z. Yan, H. Li, X. L. Xin, and J. Cao, “A secure SDN based multi-RANs architecture for future 5G networks,” Computer Security, vol. 70, pp.648-62, Sept. 2017. doi: 10.1016/j.cose.2017.08.013
[97] E. Oproiu, M. Iordache, C. Costea, C. Brezeanu and C. Patachia, “5G Network Architecture, Functional Model and Business Role for 5G Smart City Use Case: Mobile Operator Perspective,” 2018 International Conference on Communications (COMM), Bucharest, pp. 361-366, 2018. doi: 10.1109/ICComm.2018.8484747
[98] R. Guerzoni, R. Trivisonno, and D. Soldani, “SDN-based architecture and procedures for 5G networks,” 1st International Conference on 5G for Ubiquitous Connectivity, pp. 209-214, Nov. 2014. doi: 10.4108/icst.5gu.2014.258052
[99] J. Duan, C. Wu, F. Le, A. X. Liu, and Y. Peng, “Dynamic Scaling of Virtualized, Distributed Service Chains: A Case Study of IMS,” in IEEE Journal on Selected Areas in Communications, vol. 35, no. 11, pp. 2501-2511, Nov. 2017. doi: 10.1109/JSAC.2017.2760188
[100] N. T. Jahromi, S. Kianpisheh and R. H. Glitho, “Online VNF Placement and Chaining for Value-added Services in Content Delivery Networks,” 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), Washington, DC, pp. 19-24, 2018. doi: 10.1109/LANMAN.2018.8475103
[101] Service Function Chaining (SFC) Architecture, [Online]. Available: https://tools.ietf.org/html/rfc7665
[102] Problem Statement for Service Function Chaining, Available: https://tools.ietf.org/html/rfc7498#section-2
[103] IEEE Standard for Service Composition Protocols of Next Generation Service Overlay Network,” in IEEE Std 1903.2-2017 , pp.1-54, 2018.
[104] Y. Al Ridhawi and A. Karmouch, “QoS-Based Composition of Service Specific Overlay Networks,” in IEEE Transactions on Computers, vol. 64, no. 3, pp. 832-846, Mar. 2015. doi: 10.1109/TC.2013.2297306
[105] F. Paganelli, M. Ulema, and B. Martini, “Context-aware service composition and delivery in NGSONs over SDN,” in IEEE Communications Magazine, vol. 52, no. 8, pp. 97-105, Aug. 2014. doi: 10.1109/MCOM.2014.6871676
[106] L. -D. Chou, C. -W. Tseng, Y. -K. Huang, K. -C. Chen, T. -F. Ou, and C. -K. Yen, “A Security Service on-demand Architecture in SDN,” The 7th International Conference on Information and Communication Technology Convergence (ICTC 2016), Jeju Island, Korea, pp. 287-291, Oct. 2016. doi: 10.1109/ICTC.2016.7763487
[107] P. Quinn and J. Guichard, “Service Function Chaining: Creating a Service Plane via Network Service Headers,” in Computer, vol. 47, no. 11, pp. 38-44, Nov. 2014. doi: 10.1109/MC.2014.328
[108] M. Chowdhury, M. Rahman and R. Boutaba, “Vineyard: Virtual network embedding algorithms with coordinated node and link mapping,” in Networking, IEEE/ACM Transactions on, vol. 20, no. 1, pp. 206-219, Feb. 2012. doi: 10.1109/TNET.2011.2159308
[109] M. Rabbani, R. Pereira Esteves, M. Podlesny, G. Simon, L. Z. Granville, and R. Boutaba, “On tackling virtual data center embedding problem,” in IFIP/IEEE International Symposium on Inte grated Network Management (IM 2013), pp. 177-184. May 2013.
[110] A. Fischer, J. F. Botero, M. T. Beck, H. de Meer, and X. Hesselbach, “Virtual Network Embedding: A Survey,” in IEEE Communications Surveys & Tutorials, vol. 15, no. 4, pp. 1888-1906, Fourth Quarter 2013. doi: 10.1109/SURV.2013.013013.00155
[111] J. Gil Herrera and J. F. Botero, “Resource Allocation in NFV: A Comprehensive Survey,” in IEEE Transactions on Network and Service Management, vol. 13, no. 3, pp. 518-532, Sept. 2016. doi: 10.1109/TNSM.2016.2598420
[112] D. Gross, John F. Shortle, James M. Thompson and Carl M. Harris, “Fundamentals of Queueing Theory, 4th Edition,” New York: Wiley, 2008.
[113] T. Choi, T. Kim, W. TaverNier, A. Korvala and J. Pajunpaa, “Agile management of 5G core network based on SDN/NFV technology,” 2017 International Conference on Information and Communication Technology Convergence (ICTC), Jeju, pp. 840-844, 2017. doi: 10.1109/ICTC.2017.8190795
[114] L. Le, B. P. Lin, L. Tung, and D. Sinh, “SDN/NFV, Machine Learning, and Big Data Driven Network Slicing for 5G,” 2018 IEEE 5G World Forum (5GWF), Silicon Valley, CA, USA, pp. 20-25, 2018. doi: 10.1109/5GWF.2018.8516953
[115] VMware, Understanding Clones , [Online] https://www.vmware.com/support/ws55/doc/ws_clone_ overview.html

指導教授

周立德(Li-Der Chou)

審核日期

2019-8-16

推文