5G網路縮短了傳輸的時間，帶給使用者更高速且低延遲的服務。而在5G網路架構下，很多服務會包括通訊及運算兩種資源需求，因此妥善的多資源配置是提升使用者服務品質(Quality of Services, QoS)很重要的因素，而網路切片技術可依照各服務需求單獨分配其所需的資源量。目前大多數的論文都是以最小化平均延遲做為網路切片的目標，然而最小化平均延遲並無法讓使用者得到最好的QoS，因此針對各種應用的不同QoS需求，此論文中提出了一種以達成最小QoS違反機率為目標的多資源切片方法，稱之為Network Slicing with Minimum QoS Violation Probability (NS-MQV)，此方法概念為計算各服務的延遲分佈，並使用各服務流量之機率來獲得整體的QoS違反機率，然後使用次梯度搜尋演算法去找尋最佳的資源配置，以得出最小QoS違反機率。研究結果表明NS-MQV在預設環境下時，相較於無做資源切割和均等切割資源的方法，分別可改進80.57%和90.00%的QoS違反機率。同時隨著封包到達率增加，NS-MQV之QoS違反機率會有較小的上升趨勢，因而產生更好的改進。

5G網路縮短了傳輸的時間，帶給使用者更高速且低延遲的服務。而在5G網路架構下，很多服務會包括通訊及運算兩種資源需求，因此妥善的多資源配置是提升使用者服務品質(Quality of Services, QoS)很重要的因素，而網路切片技術可依照各服務需求單獨分配其所需的資源量。目前大多數的論文都是以最小化平均延遲做為網路切片的目標，然而最小化平均延遲並無法讓使用者得到最好的QoS，因此針對各種應用的不同QoS需求，此論文中提出了一種以達成最小QoS違反機率為目標的多資源切片方法，稱之為Network Slicing with Minimum QoS Violation Probability (NS-MQV)，此方法概念為計算各服務的延遲分佈，並使用各服務流量之機率來獲得整體的QoS違反機率，然後使用次梯度搜尋演算法去找尋最佳的資源配置，以得出最小QoS違反機率。研究結果表明NS-MQV在預設環境下時，相較於無做資源切割和均等切割資源的方法，分別可改進80.57%和90.00%的QoS違反機率。同時隨著封包到達率增加，NS-MQV之QoS違反機率會有較小的上升趨勢，因而產生更好的改進。

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