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研究生: 洪鵬凱
Hong, Peng-Kai
論文名稱: 彈性光網路中預先保留機制適用之二維動態資源配置與重組
On Two-dimensional Dynamic Resource Allocation with Reconfiguration for Advance Reservation 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: 55
中文關鍵詞: 彈性光網路繞徑調變與頻譜配置問題預先預約重組
外文關鍵詞: Elastic optical networks (EONs), Routing, modulation and spectrum assignment (RMSA), Advance reservation, Reconfiguration
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  • 隨著科技不斷的進步,如何讓網路承載更大的流量成為了一個相當重要的議題。在傳統的光纖波長分波多工網路將一個波長當作是一個傳輸的基本單位,在傳輸的過程當中常常會因為傳輸量的大小並沒有到達一個波長能乘載的流量而造成浪費,這種固定的且一個波長承載量大的傳輸方式漸漸地受到挑戰。近年來,因為有光正交頻分復用技術的發展,能將傳輸的量切得更為細小,且能使波與波之 間能夠有部分的重疊,大幅度的降低了浪費的傳輸空間,提升傳輸的速率,這種新型態的網路稱之為彈性光網路。
    在彈性光網路中, 依據需求到達時有沒有立即做傳輸分為兩種不同的形態,立即預約與事先預約。過去在一般的需求到達時我們會立即做配置並給予資源,這就是立即預約,而事先預約則是當需求到達時不需要立即做資源的配置,只需要將未來所需要利用的資源先標記,等到需要利用的時間點再去做配置,這就是所謂得預先預約。而近年資料備份集集大量資料的傳輸成為很熱門的應用,因此事先預約成為了相當重要的議題值得我們去討論。
    在許多事先預約的文章中總是固定傳輸開始與結束時間點,但是其實當需求到達時就可以立刻做傳輸的動作,只需要在最後傳輸時間前傳輸完成就算是一個成功的配置,因此我們將傳輸的過程變得更有彈性,當需求到達時只需要在最後傳輸時間前傳輸完成而不用固定一段傳輸的時間點。而在這之後我們思考既然能夠將傳輸時間的區塊更彈性,是不是我們也能讓傳輸的時間及每個時間點所需要傳輸的量做一個調變,因此我們文章也提出了幾個不同的策略來針對調變做選擇。最後,再透過預先預約的特性,讓還沒有真正開始的需求能夠做重組的動作,讓新進的需求能夠透過未開始的需求所做的重組能夠有空間能夠做配置,我們針對哪些需求應該要先做重組也有一些不同的策略。

    Thanks to progress of science and technology, how to make the network carrying a larger traffic has become a very important issue. A wavelength is used as a basic unit for transmission in wavelength division multiplexing networks (WDM). Resources were wasted because the size of a transmission did not reach a wavelength’s capacity. This fixed and massive transmission mode has been challenged nowadays. Because of the development of optical orthogonal frequency division multiplexing technology (O-OFDM), granularity can be cut smaller, between wavelengths can be overlapping partially. As a result, this new generation of network can reduce wasted resources, and increase transmission rate. This new generation of optical network was called Elastic Optical Networks (EONs).
    In elastic optical networks, requests are divided into two types - immediately reservation (IR) and advanced reservation (AR). When a request arrives and needs resource allocation immediately, this is called an IR request. When a request arrives and does not need immediate allocation, we only need to reserve the spectrum resources, and this is called an AR request. In recent years, data backup and large transmission has become a popular issue. Therefore, AR has become a more critical issue in the near future.
    In most AR researches, the starting and ending timeslot of a connection are fixed, but actually we can start transporting immediately when a request arrives as long as we can finish it before its deadline. As a result, we can make transmission more flexible, we do not limit the starting and ending timeslot for a request. Since we can make transmission time more flexible, we may modify a request’s service duration and rate. Therefore, we propose different policies to modify a requests service duration and rate. Finally, we do reconfiguration for AR requests, and the reconfiguration process makes the spectrum resource smoother. Thus, the blocking probability (BP) can be reduced. In this paper, we also proposed a few of policies for AR reconfiguration.

    摘要 III Abstract V 致謝 VII Content VIII List of Figures X List of Tables XI 1. Introduction 1 2. Background 4 2.1. Wavelength-Division Multiplexing (WDM) 4 2.2. Elastic Optical Networks (EONs) 5 2.2.1. Orthogonal Frequency-Division Multiplexing (OFDM) 5 2.2.2. Optical Frequency Representation 5 2.2.3. Modulation Format 6 2.2.4. Routing, Modulation and Spectrum Assignment (RMSA) 8 2.2.5. Reconfiguration 9 2.2.6. Advanced Reservation 10 3. Related Work 12 3.1. Delayed Spectrum Allocation (DSA) 12 3.2. Flow Chart of DSA 13 4. Propose Scheme 17 4.1. Motivation 18 4.1.1. Flexible Spectrum Resources Block 18 4.1.2. Shape Adjustment 20 4.2. Shape Determination Policies 21 4.2.1. Larger Spectrum First (LSF) 21 4.2.2. Longer Service Duration First (LSDF) 23 4.3. Dynamic Delayed Spectrum Allocation (DDSA) 25 4.3.1. Flow Chart of DDSA 25 4.3.2. DDSA algorithm 28 4.4. Sorting Policies 32 4.5. Complexity Analysis 33 5. Performance Evaluation 35 5.1. Parameter Settings 35 5.2. Performance Matrices 36 5.3. Simulation Results 36 5.3.1. Performance of Blocking Probability 36 5.3.2. Performance of RMSA Time 48 6. Conclusion 51 References 53

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