臺灣博碩士論文加值系統

由於使用者以手機透過無線網路到雲端資料中心存取應用的傳輸過程中會產生極高的傳輸延遲，因此5G網路提出行動邊緣運算的概念，在基地台附近提供雲端計算的能力，讓手機應用服務業者可以將手機應用服務從雲端搬到離使用者更近的MEC中來降低延遲。然而，許多熱門的行動應用服務多屬於多媒體影音服務，使用者在存取該應用服務時，會導致MEC伺服器產生大量的場景渲染和影音編碼等高計算量的任務，因而產生極高的功耗。然而MEC的架構和雲端資料中心的架構不同，使得傳統在雲端資料中心的省電機制無法在MEC伺服器上有效的運用。
因此，本論文提出一個針對MEC架構設計的有效MEC伺服器節能管理機制。本論文分別針對三種不同狀態(忙碌狀態Hotspot、閒置狀態Idle以及可用狀態Active)下的MEC伺服器，設計不同的省電管理機制，以期達到MEC伺服器最佳的省電效率。模擬實驗結果顯示，透過我們的方法可以保持與無省電機制的MEC有相同的性能，並且降低忙碌狀態和閒置狀態的MEC伺服器數目，實現更好的能源效率與負載平衡。

When users access mobile cloud applications by using smartphones, the transmissions between the radio access network (RAN) and the remote cloud will generate high latencies. Hence, mobile edge computing (MEC) is proposed to provide the capacity of cloud computing with the RAN in close proximity to mobile subscribers in 5G network. Mobile application providers can move data from the cloud to MEC servers for shortening latency. However, most popular mobile applications are multimedia applications. When users access these multimedia applications, MEC servers must process a lot of rendering and encoding tasks to generate high power consumption. Previous power-saving studies in the cloud are not suitable for MEC servers because of the different architecture of MEC.
In this paper, we propose an adaptive power-saving management scheme for MEC. We design three different strategies for different states of MEC servers (hot state, idle state, and normal state) while maintaining high usage for MEC servers. The simulation results show that our algorithm can maintain similar performance as MEC without any power-saving mechanism. It also reduces the number of idle servers and busy servers to achieve better energy efficiency and load balancing.

誌謝 i
摘要 ii
Abstract iii
目次 iv
表目次 v
圖目次 vi
第一章 緒論 1
1.1 簡介 1
1.2 研究動機 5
1.3 論文架構 7
第二章 背景知識 8
2.1 何謂行動邊緣運算(Mobile Edge Computing) 8
2.2 MEC省電機制相關研究 16
第三章 研究方法 21
3.1 系統模式 21
3.2 設計方法 27
3.2.1 忙碌MEC伺服器處理演算法 28
3.2.2 閒置MEC伺服器處理演算法 34
3.2.3 取得可用MEC伺服器處理演算法 37
3.2.4 流量導向演算法 39
第四章 實驗結果 41
4.1實驗環境參數 41
4.2平均反應時間和符合QOS的比例 46
4.3忙碌和閒置MEC伺服器數目和睡眠MEC伺服器數目 50
4.4整體MEC系統功耗 54
第五章 結論 55
參考文獻 56

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