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研究生:程奎賀
研究生(外文):KUI-HE CHENG
論文名稱:大規模軟體定義網路之多控制器負載平衡策略研究
論文名稱(外文):Load-Balancing Multiple Controllers Mechanism for Large-Scale Software-Defined Networking
指導教授:陳俊良陳俊良引用關係
指導教授(外文):Jiann-Liang Chen
口試委員:陳俊良
口試委員(外文):Jiann-Liang Chen
口試日期:2014-07-02
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:電機工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:英文
論文頁數:72
中文關鍵詞:軟體定義網路負載平衡多控制器階層式控制中介控制
外文關鍵詞:Software-Defined NetworkingLoad BalancingMultiple ControllersHierarchical ControlMeta Control
相關次數:
  • 被引用被引用:0
  • 點閱點閱:338
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  • 下載下載:66
  • 收藏至我的研究室書目清單書目收藏:1
軟體定義網路(Software-Defined Networking, SDN)技術提出了一種將網路控制平面和資料平面分離的新型網路架構,使管理者更易於控管網路,替網路新應用和未來網際網路技術提供了一種新的解決方案。在SDN 網路中,整體網路之效能與SDN控制器有著重要的關聯性,但是隨著網路規模不斷擴增,集中控制器在可擴展性方面的問題受到許多專家學者的質疑。為了解決SDN網路集中控制器面臨的問題,研究學者們紛紛針對此議題提出解決方案。因此本研究聚焦在大規模軟體定義網路之多控制器負載平衡策略,透過中介控制器(Meta Controller)之方法實現控制平面流量分配機制,以達到SDN多控制器網路最佳效能之目標。

本研究致力於大規模軟體定義網路之多控制器負載平衡策略,該研究將控制平面分為中介控制平面(Meta Control Plane)及本地控制平面(Local Control Plane),建立階層式控制平面,由中介控制平面分析本地控制平面,建立效能分析機制,藉以分析本地控制器資源使用狀態,並同時建立中介控制器管理機制,實現本地控制平面運算之負載平衡,使本地控制器能提供資料平面最佳處理效能,藉以打破SDN集中控制器於大規模網路處理之瓶頸。

本研究提出一套大規模軟體定義網路之多控制器負載平衡機制,並進行以下研究分析。首先,針對提出之中介控制器管理機制進分析,於本地控制器設立門檻值進行機制研究,根據本研究結果顯示,本研究所提出之管理機制可有效監控負載過高之本地控制器。其次,針對所提出之本地控制平面排程機制進行分析,根據研究結果顯示,透過本機制有效平衡多控制器之負載,並於網路吞吐量上與集中控制器環境相互比較,改善12.7 %,以及未使用本機制之多控制器環境下,改善9.2 %。
Software-Defined Networking (SDN) is a new method for networking that has the potential to have a great impact on today's internet technology. Key aspects of SDN include the separation of data and the control plane. SDN architecture facilitates the management of complex networks and provides a new solution for network applications and future Internet technology. The network performance of SDN networks is importantly determined by with SDN controller. As the size of networks continues to increase, the issue of the scalability of the centralized controller becomes increasingly important. Researchers have proposed some solutions to this problem. In this work, a meta-controller manages the local control plane to develop an SDN network environment with multiple controls, to improve relative to central control network performance.

This work develops a load-balancing mechanism in a multiple-controller SDN network environment to implement a hierarchical control plane with a meta control plane and a local control plane. The meta control plane analyzes the resources and utilization of the local control plane to optimize processing performance. This mechanism supports the load balance of the local control plane to optimize data plane performance and overcome the bottleneck of the centralized control of a large-scale network.

This work analyzes the proposed load-balancing mechanism in a multiple-controller SDN network environment. First, the threshold of the local controller with a MC-based manager mechanism is analyzed. The results demonstrate that the MC-based manager mechanism effectively monitors the loading of the overloaded local controller. Second, the proposed local control plane scheduling is analyzed. Based on the results thus obtained, the proposed local control plane scheduling balances the loadings of the multiple controllers and improves the network throughput by 12.7 % and 9.2 % over those achieved using a centralized controller and multiple controllers without a scheduling mechanism.
摘要 I
Abstract II
致謝 IV
Contents V
List of Figures VII
List of Tables IX
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Contribution 3
1.3 Organization of Thesis 4
Chapter 2 Background Knowledge 5
2.1 Software-Defined Networking 5
2.2 OpenFlow 6
2.3 OpenFlow Switch 8
2.4 Secure Channel 8
2.5 Controller 9
2.6 Distributed Control in SDN 11
Chapter 3 Proposed Meta Controller Mechanism 13
3.1 System Overview 13
3.2 System Operation and Architecture 15
3.3 Load Balancing Module 16
3.3.1 Meta Control Plane 17
3.3.2 Local Control Plane 18
3.3.3 Problem Formulation for Hierarchical Control Structure 20
3.3.4 Flow chart and algorithm of MC-based Manager Mechanism 27
Chapter 4 System Design and Performance Analysis 34
4.1 System Design 34
4.1.1 Mininet Design 34
4.1.2 SDN Controller Design 39
4.2 System Implementation 40
4.2.1 CPU Profile 41
4.2.2 Traffic Profile 42
4.2.3 System Emulation 43
4.3 Performance Analysis 45
Chapter 5 Conclusion and Future Work 54
5.1 Conclusion 54
5.2 Future Work 55
References 57
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