| DC 欄位 |
值 |
語言 |
| DC.contributor | 資訊工程學系 | zh_TW |
| DC.creator | 史碩三 | zh_TW |
| DC.creator | Shuo-San,Shih | en_US |
| dc.date.accessioned | 2017-8-22T07:39:07Z | |
| dc.date.available | 2017-8-22T07:39:07Z | |
| dc.date.issued | 2017 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=104522049 | |
| dc.contributor.department | 資訊工程學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 近年來,網絡功能虛擬化(NFV)的技術被提出,並用來將網絡功能與底層 的硬體分開,以軟體方式提供網路加值服務功能。另外一方面,服務功能鏈(SFC) 的概念也被提出,用來讓端到端之間的網路訊務流依照特定順序經過一些加值網 路服務後才到達目的地。服務功能於資料中心中的部署策略,會十分顯著的影響 服務功能鏈的效能。本論文致力於研究混合式 NFV 環境中的服務功能部署問題, 這種部署環境是資料中心從傳統網路轉變為 NFV 網絡過渡期間的一種替代方案。
本論文所提出的 GASFP 是一種高效能的部署策略,用於最佳化混合式 NFV 環境中的服務功部署以及鏈結。GASFP 結合 GA(基因演算法算法)和貪婪最廣 度優先搜尋演算法,減少為了提供 SFC 服務而導致資料中心計算資源的浪費, 並找到一個用以減緩不適當的服務功能部署而造成延遲增加的解決方案。模擬結 果顯示,與其他 3 種演法:BINPacking,GKMSFP 以及 VCD 相比,GASFP 無 論是在混合式NFV環境或是純NFV環境中,在服務功能路徑的平均延遲和VNF 部署成本的表現上,均表現出最佳的效能。
本論文還在 XenServer 中設計並實作了一服務功能雲端平台,以及一個名為 NSHSFC 的 SFC 導向機制,以驗證本論文所提出的演算法以及實驗環境比先前 的相關研究更為全面以及真實。 | zh_TW |
| dc.description.abstract | In recent years, the network functions virtualization (NFV) was proposed to separate network functions from the underlying hardware to provide value-added service functions with software. The concept of service function chain (SFC) architecture has also been proposed, which allow traffic pass through some value-added network functions between end-to-end services. The placement of the service functions in data centers significantly affects the performance of SFC. We study the service function placement problem in hybrid NFV environment, which is an alternative plan during the transition from traditional networks to NFV networks in data centers.
We present GASFP, a high-performance approach for optimizing service function placement and service chaining in hybrid NFV environment. GASFP combine GA (Genetic Algorithm) and Greedy best-first search algorithm to reduce the waste of data center computation resource for providing SFC services and find a good solution to slow down the growth of delay from unsuitable service function placement. Simulation results show that when compared with other 3 algorithms: BINPacking, GKMSFP and VCD, GASFP has the best performance of average delay and VNF placement cost no matter in hybrid NFV environment or pure NFV environment.
We also implement a service function cloud platform and a SFC steering mechanism named NSHSFC in XenServer to verify our works are more comprehensive and realistic than the former works.
Keyword: Software-defined Networking; Service Function Chain; Network Function Virtualization; service function placement; genetic algorithm | en_US |
| DC.subject | 軟體定義網路 | zh_TW |
| DC.subject | 服務功能鏈 | zh_TW |
| DC.subject | 網路功能虛擬化 | zh_TW |
| DC.subject | 服務功能部署 | zh_TW |
| DC.subject | 基因演算法 | zh_TW |
| DC.subject | Software-defined Networking | en_US |
| DC.subject | Service Function Chain | en_US |
| DC.subject | Network Function Virtualization | en_US |
| DC.subject | service function placement | en_US |
| DC.subject | genetic algorithm | en_US |
| DC.title | 具有混合式NFV環境部署策略的服務功能雲端平台 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | A Service Function Cloud Platform with Hybrid NFV Environment Placement Strategy | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |