博碩士論文 105523015 詳細資訊




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姓名 韓學海(Xue-Hai Han)  查詢紙本館藏   畢業系所 通訊工程學系
論文名稱 霧雲網路中高效緩存分配
(Efficient Cache Assignment in Fog-Cloud Network)
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摘要(中) 第五代(5G)無線通訊的重點要求包含了高的能量使用率,以及高頻譜使用效率和低延遲的需求。近年來大量成長的動電話伴隨著大量網路內容,例如社交媒體,將帶給無線接入網路很大的挑戰。雲無線接取網路(C-RAN)結合霧運算(Fog computing)的概念已經成為成為第五代移動通訊系統(5G)的關鍵技術。 霧雲網路結合了霧運算及無線接取網路的優勢,可以在有限制的儲存空間下,將熱門資料緩存在基於霧運算的接取點(F-AP)中。因為C-RAN中包含高功率基地台(HPN),其覆蓋範圍大,可確保服務到霧運算接取點所接觸不到的用戶。近年來使用者對延遲的需求日益提升,如何在霧雲網路中減少本地用戶拿取資料的延遲是我們關住的焦點。因此本文提出了延遲感知緩存指配方法(Latency-aware caching assignment scheme),此方法可以準確的統計出本地用戶所需要的資料,同時考慮每個用戶當下的傳輸通道品質,也就是傳輸速率,找出最適合的資料及儲存在最好的霧運算的接取點(F-AP)。
實驗結果說明了減少延遲最好的方法就是減少使用雲端的次數,透過我們提出的方法,大幅減少用戶了使用雲端取得資料的次數,並可以有效的降低整體網路的延遲。
摘要(英) The fifth generation (5G) wireless communication involves many features such as high-energy efficiency, high spectrum efficiency, and low latency. The Internet contents are increasing like the content that generated by users in social media, which brings a big challenge to Radio Access Network (RAN). Using Fog-cloud network that takes the advantages of Fog computing and C-RAN, is one of the key techniques for the Fifth-Generation (5G) Mobile Communications System. Fog-cloud network is capable of caching the popular contents in the Fog computing based access points (F-APs) under limited storage capacity. Furthermore, the High Power Node (HPN), the devices in the cloud radio access network (C-RAN), assures that all of the users will be serviced by its broad coverage area. In the recent years, the user’s demand for the latency has been increasing. How to reduce the latency of local users to retrieve contents in a fog- clouds network is the focus of our attention. Our work proposes the Latency-aware caching assignment scheme, which is helpful to calculate and organize the contents that users need. Based on the quality of the user’s channel, as known as the transmission rate, this scheme finds out the contents that fully meet users’ requirements and stores the contents in the most suitable F-AP. The results show that the best way to decrease the latency is by reducing the frequency of accessing the cloud service. This scheme has been significantly reduced the frequency of accessing the cloud service, and overall network delay also been effectively declined.
關鍵字(中) ★ 霧雲網
★ 緩存
★ 低延遲
關鍵字(英) ★ Fog-Cloud Network
★ Caching
★ Low Latency
論文目次 Table of Contents
1 Introduction ......1
1.1 Background . . . . . . . 1
1.2 Motivation . . . . . . 2
1.3 Contribution . . . . . . . 2
1.4 Framework . . .... 3
2 Background of Cloud and Fog and Related Works ......4
2.1 Fog-Cloud Networks . . ..... 4
2.1.1 Cloud Radio Access Networks . .....4
2.1.2 Fog Network . . .... 5
2.1.3 Fog-Cloud Networks . . ..... 7
2.2 Related Work . . .....9
2.2.1 Fog and Cloud Computing Combination with IoT Application . . .... 9
2.2.2 Cache Technology and Fog Network . . .... 11
3 Fog-Cloud Networks ......14
3.1 System Model ...... 15
3.1.1 Construct Network ...... 15
3.1.2 Request Contents Distribution . . . . . .. 18
3.1.3 Caching Policies . . . . . . 19
3.1.4 Transmission Decision . . .... 20
3.1.5 Task Latency . . . ... 21
3.2 Problem Formulation . ..... 23
4 Latency-Aware Caching Assignment Scheme ......24
4.1 Select F-AP as candidate list and sent the request task . . . . . . . 25
4.2 Calculate the score of contents . ... . . . 26
4.3 Different perspectives . . . . . . . 27
4.4 Introduce Weight Discussion . . . . . . 29
4.5 Normalization Gap weight . . . ... 30
5 Performance Evaluation 33
5.1 Latency time Perfornamce Evaluation . . . . . . 35
5.2 Compare the Proportion of Using Cloud and Fog . . . ... 37
6 Conclusion and FutureWork ......40
6.1 Conclusion . . . . . . 40
bibliographystyle......41
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指導教授 黃志煒(Chih-Wei Huang) 審核日期 2018-8-16
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