不同時限任務於多邊緣計算伺服器之排程與分配策略研究

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姓名

陳子齊(Tzu-Chi Chen) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

不同時限任務於多邊緣計算伺服器之排程與分配策略研究
(Study of Schedule and Arrangement Policy for Different Time Constraint Tasks in Multiple Mobile Edge Computing Servers Environment)

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摘要(中)

隨著時代進步，裝置的種類及數量快速增長，裝置要處理的任務種類更是繁複多變，各個任務所需的執行時間長短不一，計算量可能超出裝置能負荷的能力，故無法滿足計算量大、且需要在時限內完成任務的需求。裝置可以利用雲端運算服務，將裝置上無法完成的任務，透過網路上傳至雲端伺服器，借助伺服器強大的運算能力，快速完成任務並將結果回傳。現今裝置接收任務的延遲需求更加的低，將任務傳輸到遙遠的雲端伺服器進行運算所需的額外傳輸延遲，可能會導致任務無法在時限內完成，因此有人提出了邊緣運算來解決這項問題。
邊緣運算為運算伺服器且更貼近裝置端，裝置透過更短的傳輸時間將任務傳送至伺服器，以達到任務延遲要求。以4G LTE為例，邊緣運算伺服器架設於4G基地台旁，使用者可以透過行動網路，將裝置的任務卸載(Offload)至邊緣運算伺服器做運算並將結果回傳，稱為行動邊緣運算(Mobile Edge Computing)。
本論文提出的Time Constraint-based Task Scheduling for Multi-Server (TCTSMS)，將邊緣運算伺服器接收的任務依據模糊理論，將任務分配至鄰近有空閒的伺服器進行運算，以降低自身負載，使邊緣運算伺服器接收並完成更多的任務、降低任務拒絕率。任務接收策略分為兩種方法：搶奪(Preemptive)以及非搶奪(Non-preemptive)，搶奪可讓延遲需求較緊急的任務插隊於能容忍較長延遲的任務之前，使較緊急的任務能及早執行，不會因為被能容忍較長延遲的任務較多，而造成排隊時間過長或因此被伺服器拒絕接受任務；本論文假設了任務提出的計算需求與實際執行時會有所差異而可能導致超時，更能貼近現實任務卸載的不確定因素。

摘要(英)

As the evolution of technology, more and more devices are innovated. Device have wide variety of task. Some Tasks need to be executed in delay constraint time. Device may not satisfy task’s demand of delay because of low CPU capacity of device. If device can not satisfy task’s demand, device can offload the task to cloud server through network. Offload task to cloud will cause transmission time between server and device. Cloud server has powerful CPU to help device executed task, but the transmission time is too long to fulfill delay constraint.
Edge Computing is a kind of offloading method but more closed to user. For instance, Mobile Edge computing will deploy the server near by the LTE base station. Device can offload task to edge server through 4G LTE network. Task only needs short transmission time to complete delay sensitive task by offload task to edge server.
This paper proposes Time Constraint-based Task Scheduling for Multi-Server (TCTSMS) algorithm. TCTSMS Algorithm use fuzzy theory to choose task will be executed at local server or offload to other idle server with set of edge server. If one server has many offload task requests as hotspot, total throughput will increase and blocking rate decrease. This paper proposes preemptive method to ensure delay sensitive task would not be blocked because of lots of task with long delay tolerance occupy edge computing system. This paper assumes that the task provides information of required execution cycle is not equals to real execution cycle. This uncertainty situation may be closer to reality.

關鍵字(中)

★ 行動邊緣運算
★ 多伺服器任務分配
★ 模糊理論

關鍵字(英)

★ Mobile Edge Computing
★ Multi Server Task Allocation
★ Fuzzy Theory

論文目次

摘要 I
ABSTRACT II
致謝 III
目錄 IV
圖目錄 VI
表目錄 IX
1. 第一章緒論 1
1.1 研究背景 1
1.2 研究動機與目的 1
1.3 章節概要 2
2. 第二章相關研究背景 3
2.1 LTE架構基本介紹 3
2.1.1 LTE換手介紹 7
2.2 雲端運算基本介紹 9
2.3 邊緣運算(Edge Computing) 11
2.3.1 行動邊緣運算(Mobile Edge Computing) 13
2.3.2 雲塊運算(Cloudlet Computing) 14
2.3.3 霧運算(Fog Computing) 15
2.4 模糊理論(Fuzzy Theory) 17
2.5 相關文獻 18
3. 第三章研究方法 20
3.1 系統架構 20
3.2 系統流程 25
3.2.1 系統參數 25
3.2.2 邊緣運算伺服器不可搶先排程運作流程 27
3.2.3 邊緣運算伺服器不可搶先排程Local/Remote決策運作流程 30
3.2.4 邊緣運算伺服器可搶先排程運作流程 33
3.2.5 邊緣運算伺服器可搶先排程Local/Remote決策運作流程 37
4. 第四章模擬結果與討論 42
4.1 模擬環境 42
4.2 模擬參數 42
4.3 模擬結果比較 43
4.3.1 伺服器預測不同運算cycle之效能影響分析 43
4.3.2 單伺服器不同Delay Sensitive Task 比率之影響分析 46
4.3.3 單伺服器不同DST Ratio以及Number of UE之影響分析 50
4.3.4 多伺服器不同Number of UE之影響分析 58
4.3.5 多伺服器不同Number of UE於Hotspot之影響分析 62
4.3.6 多伺服器不同Number of UE於整體環境之影響分析 66
4.3.7 多伺服器不同Delay Sensitive Task比率於Hotspot之影響分析 69
5. 第五章結論 72

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指導教授

陳彥文(Yen-Wen Chen)

審核日期

2021-8-2

推文