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研究生: 郭儲嘉
Kuo, Chu-Chia
論文名稱: 彈性光網路中利用基於層化圖模型之時間頻譜資源管理於預先保留機制之探討
On Advance Reservation with Layered-Graph-Model-based Time-Spectrum Resource Management in Elastic Optical Networks
指導教授: 許靜芳
Hsu, Ching-Fang
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2017
畢業學年度: 105
語文別: 英文
論文頁數: 56
中文關鍵詞: 彈性光網路預先保留繞徑與頻譜配置問題二維資源模型三維資源模型輔助圖層化圖
外文關鍵詞: Elastic optical networks (EONs), Advance reservation (AR), Routing and spectrum assignment (RSA), two-dimensional resource model, three-dimensional resource model, auxiliary graph, layered-graph
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  • 隨著科技日新月異,各式各樣的應用不斷的發展,網路的使用量以及速率需求持續增長,因此傳統的光纖網路─波長分波多工網路由於其剛性的粒度限制,無法有彈性的配置適合大小的資源給予需求,進而造成資源的浪費以及降低頻譜的使用效率,因此利用光正交分頻多工技術的彈性光網路被提出,此技術使載波彼此能夠部分重疊並保持正交,因此不需固定以單一波長為單位配置,可以大幅提升資源使用的彈性,使得頻譜資源能夠更有效的利用,提升頻譜的利用率。
    近年來,許多基於資料中心的應用快速發展,如資料備份、網格計算等高資料量傳輸的需求,其需要大量頻寬的使用,但沒有嚴格的時間限制,因此一個新穎的服務請求被提出來,稱為預先保留請求。預先保留請求到達時,會給予其最晚服務完成時間,只要在該時間前完成傳輸即可,因此可以彈性的利用不同時間點的頻譜資源,以達到頻譜的最佳使用狀況,進而提升頻譜利用率,增加網路傳輸的效能。
    繞徑與頻譜配置是彈性光網路中的重要議題,此問題分為兩個部分:繞徑選擇以及頻譜配置的選擇,先前的研究大都著重在繞徑與頻譜配置的最佳選擇,而利用地毯式的搜索,逐一找出每種繞徑與頻譜配置的方案,這種方式雖然能夠找到相當好的解,但往往需要耗費極大的時間。因此本篇論文提出一個在三維資源模型下,利用層化圖的方式來描述頻譜資源使用情況,並利用此層化圖來尋找繞徑與頻譜配置的解,縮短搜尋時間以及增加效能。
    模擬結果顯示,在相同的繞徑與頻譜配置決策下,層化圖模型與傳統資源模型能夠達到相同效能,並且獲得大量的時間改善。而在不同的繞徑決策下,層化圖模型能夠以少量的時間,來達到大量的效能改善。

    With the growing technology, various applications are developed. The amount of the network used and the requirement of the network speed increase. The traditional optical networks, Wavelength-Division Multiplexing (WDM) optical networks, are unable to flexibly allocate the appropriate size of the resources for the request due to its rigid granularity. Thus causing the waste of resources and reduce the spectrum utilization. Therefore, optical Orthogonal Frequency-Division Multiplexing (O-OFDM)-based elastic optical networks (EONs) is proposed. With the O-OFDM technology, the subcarriers can partial overlap with each other. So there is no need to allocate resources in a single wavelength unit. That can greatly enhance the flexibility of the use of resources, and make the use of the spectrum resources more effective. Then increase the spectrum utilization.
    Recently, the datacenter-based applications, such as data backup and grid-computing, are rapid development, which require high demand for data transmission. Although these applications need lots of bandwidth to use, they do not have strict time limits. Therefore a novel service request, named advance reservation (AR) request, is proposed. When AR requests arrival, they need to give their deadline time. As long as the transmission is completed before the deadline time, this is a successful transmission. With this feature, it can flexibly use different time spectrum resources to achieve the optimal use of the spectrum resources. Thereby increasing the spectrum utilization and network performance.
    Routing and spectrum assignment (RSA) problem is an important issue in elastic optical networks. This problem divide to two parts: routing path selection and spectrum assignment scheme. Previous studies focus on finding the optimal RSA solution. In order to find optimal solution, they use iterative searching to find all RSA solution. Then they select the optimal ones as the result. Although this way can find optimal solution, it always spends lots of time to search. Therefore, we propose an RSA algorithm, which use the layered-graph to describe the spectrum situation, to find optimal solution in three-dimensional resource model. Thereby reduce the searching time and increase the network performance.
    Simulation results show that the layered-graph-model-based algorithms can achieve the same performance and obtain lots of time improvement as compared with previous work in the same RSA decision. In the different routing decision, layered-graph-model-based algorithm can use a small amount of time to achieve a lot of performance improvement.

    摘要 I Abstract III 致謝 V Content VI List of Figures VIII List of Tables IX 1. INTRODUCTION 1 2. BACKGROUND 4 2.1. Elastic Optical Networks (EONs) 4 2.1.1. OFDM Technology 4 2.1.2. Routing and Spectrum Allocation (RSA) 5 2.2. Advance Reservation (AR) 6 3. RELATED WORK 9 3.1. Maximize Total Link TSC (MTLT) 9 3.2. Spectrum-Scan Routing (SSR) / Spectrum Window Plane (SWP) 12 3.3. Layered-Graph-Based RSA 13 3.3.1. Layered-Graph Model 13 3.3.2. Filter Graph 14 4. PROPOSED SCHEME 17 4.1. Motivation 20 4.2. Layered-graph-model-based k-shortest Paths (LG_KSP) 20 4.3. Layered-graph-model-based Exhaustive Routing (LG_ER) 30 4.4. Layered-graph-model-based Exhaustive Routing with Pre-calculation (LG_ER + pre.) 38 4.5. Complexity Analysis 39 4.5.1. Time Complexity 39 4.5.2. Space Complexity 41 5. PERFORMANCE EVALUATION 43 5.1. Parameter Settings 43 5.2. Performance Metrics 43 5.3. Simulation Results 44 5.3.1. MTLT vs. KSP 44 5.3.2. KSP vs. SSR_KSP and LG_KSP 47 5.3.3. KSP vs. SSR_ER (+ pre.) and LG_ER (+ pre.) 48 5.3.4. Space Consumption 51 6. CONCLUSION 53 Reference 54

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