網路切片自提出便被視為第五代行動通訊網路(5G)的關鍵技術,預期能實 現 5G 時代多樣化的應用需求和垂直產業。建基於集中式無線接取網路、軟體定義 網路和網路功能虛擬化等技術上的突破,網路切片將實體網路虛擬邏輯化,進而劃 分成不同服務的可行性已被證實,是一個更具效率、彈性及可靠性的架構。 然而,由於缺乏有效且全面性的資源分配機制,要達成網路協作仍存在挑戰。 本篇研究便以此為出發點,提出一個站在網路協作者角度的傳遞路徑與運算資源 管理情境,以期能動態地切割與配置端對端獨立網路切片去滿足企業的垂直需求。 而此複雜的問題更進一步被我們設計成數學模型,目標為最大化整體收益。我 們利用拉格朗日鬆弛法來解決此模型,並且發展一個以拉格朗日鬆弛法為基礎的 啟發式演算法來求得可行解。最後,透過一系列包含多元需求以及不同實體網路建 置環境的實驗,此演算法也被證明具有最佳化資源利用的能力。
Network slicing is viewed as an emerging paradigm for satisfying diverse applications and vertical industries which are 5G network anticipated to empower. Based on architectural breakthroughs such as C-RAN, SDN, and NFV, the concept offering network slices with independent control as services over a common physical infrastructure is proved to be practicable and able to better make use of resources. However, challenges remain in achieving network orchestration due to the lack of a comprehensive resource management approach. Therefore, a traffic path and computing power assignment problem of network slicing from an orchestrator viewpoint is presented in this thesis. The objective of the orchestrator is to dynamically allocate resources and gain maximum rewards by satisfying E2E slicing requests of vertical companies. The complex problem is further formulated to a mathematical model and optimally solved by adopting Lagrangian relaxation method. Moreover, a Lagrangian relaxation- based approach with the Drop-and-Add algorithm is proposed for fulfilling E2E slices and get optimal feasible solutions. At last, the developed solution approach is validated by computational experiments to be effective to manage resources when facing diverging QoS requirements and different network infrastructure.