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

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曾家偉(Chia-Wei Tseng) 查詢紙本館藏

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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)

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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

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指導教授

周立德(Li-Der Chou)

審核日期

2019-8-16

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