在彈性光網路中，利用光正交分頻多工的技術，使得頻譜配置時，能夠依照使用者傳輸量的需求，彈性的配置適合的資源大小。隨著多元的網路應用發展，資料傳輸量日益增加，空間分割多工之彈性光網路中，加入空間維度資源的概念，藉由多核光纖的多個傳輸空間進行傳輸，提升資料傳輸量。
根據使用者需求抵達系統時，是否立刻進行傳輸服務區分為兩種需求類型：立即保留及預先保留。抵達系統需要立即進行傳輸服務的需求，稱之為立即保留需求；然而，需求抵達系統時，預約一段未來的時間區間進行傳輸服務，則稱為預先保留需求。在預先保留需求配置時，需求結束時間以前完成傳輸服務即為成功配置，因此彈性調整傳輸時間區間及每一個時間點傳輸的資料量，能有效地利用頻譜資源。
繞徑核心與頻譜配置是空間分割多工之彈性光網路中的重要議題，過去的研究中，耗費大量時間計算每一種繞徑、核心與頻譜配置，以尋找最佳配置選擇。本篇論文在時間、光纖鏈結核心與頻譜三維資源模型下，生成層化圖記錄資源使用情形，再利用層化圖資訊來搜尋繞徑核心與頻譜配置的解，減短尋找計算時間。
模擬分析中，不同規模的網路拓撲環境，比較層化圖模型頻譜資源管理與過去的研究方法，在使用者需求配置阻斷機率有相近的表現，然而，節省大量的執行計算時間。也比較層化圖模型頻譜資源管理下，不同繞徑策略，影響使用者需求配置阻斷機率與執行時間花費的差異。

The support of optical orthogonal frequency division multiplexing (O-OFDM) technology in elastic optical networks (EONs), according to user requests’ data transmit volume, provisioning appropriate spectrum resources become more flexible. With the development of various network application, data transmit volume extremely increase day by day. In spatial division multiplexing elastic optical networks (SDM-EONs), add the concept of space dimension resources. One type of fibers used in SDM-EONs, multicore fiber (MCF) propagate data through multiple core. Achieve the goal of more data volume transmission.
There are two type of user requests. Depending on whether the requests be served immediately on arrival. When the user requests arrive system, starting transmission service at once or reserving the spectrum resources within a future time period, called immediate reservation (IR) and advance reservation (AR) respectively. As long as we complete the transmission service before the requests deadline, these requests can be count in success provision. Adjusting the service time period and data transmit volume at each time slot during transmission service time could exploit the resources effectively.
Routing, core and spectrum assignment (RCSA) problem is an important issue in SDM-EONs. Previous studies spend long time on calculating routing, core and spectrum assignment for each possible choice and choosing the best solution. We propose a three-dimensional resource model, including time, fiber link core, and frequency domain. Generate layered-graph to note the spectrum usage situation. Search the routing, core and spectrum assignment solution by this layered-graph information and reduce the computational time.
In different scale network topology, simulation analysis compare layered-graph-model-based spectrum resource management to previous studies method. The former achieves similar performance in terms of user requests blocking probability (BP) and saves lots of execution time. On layered-graph-model-based spectrum resource management, analysis also show the impact of different routing strategy on BP and execution time.

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