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研究生: 莊景舜
研究生(外文): Chuang, Chin-Shun
論文名稱: RED佇列管理機制對VoIP服務品質之影響分析
論文名稱(外文): Study of VoIP Service Quality in Control of RED Management
指導教授: 洪盟峰
指導教授(外文): Horng, Mong-Fong
學位類別: 碩士
校院名稱: 樹德科技大學
系所名稱: 資訊工程學系
論文出版年: 2006
畢業學年度: 94
語文別: 中文
論文頁數: 59
中文關鍵詞: 佇列管理類神經網路
外文關鍵詞: Queue ManagementVoIPNeural Network
相關次數:
  • 被引用:0
  • 點閱:12
  • 評分:*****
  • 下載:0
  • 書目收藏:0
VoIP已經成為現今網際網路最重要的服務之ㄧ,因此VoIP的品質保障技術也變的十分重要。本文的重點在探討ADSL路由器中,當使用RED佇列管理機制時,對於VoIP服務品質的影響。RED機制是藉由設定佇列的高、低臨界值以及丟棄率等參數,來決定何時、如何丟棄佇列內的封包,以避免過長以及過度變動的佇列所造成的等待延遲及延遲抖動。但是RED參數的決定,向來會因為網路品質的需求,例如延遲及延遲抖動的要求的不同而有所異,所以如何針對VoIP服務品質來決定路由器內RED佇列的操作參數,將是本文的研究重點之ㄧ。我們利用逆傳導類神經網路來學習決定RED機制參數的設定,在此網路模型,將以可容許延遲以及路由器頻寬為輸入,以RED機制參數為輸出,並藉由輸入出變數的關係推導取類神經網路的訓練樣本。模擬結果顯示,即使在低頻寬或非對稱式的傳輸環境下,本方法能夠有效地改善VoIP服務封包的延遲與抖動,藉由本文的成果可以提供網路或程式設計人員與ISP業者,在使用RED佇列管理機制時,於路由器設定的參考,建構出具有能適應VoIP訊務型態的佇列管理。
The quality issue of VoIP service is significantly attractive, since VoIP has become a promising service on Internet. In this thesis, the effectiveness and performance of random early detection (RED) applied on ADSL routers to control VoIP service quality are investigated. In RED, the drop probability, maximum and minimum thresholds are three operational parameters to determine when and how to drop the packets in the queue of routers. The proper packet dropping will be helpful to reduce the queuing delay and jitter of VoIP packets caused by over-flow and high variation of packet queues. Additionally, the determination of operational parameters depends on the requirement of quality-of-service (QoS), for example differentiated delay and delay jitter. Thus how to determine the parameters is investigated in this thesis. A back-propagation neural network is proposed to learn the specifying the RED parameters. The inputs of this neural network are delay tolerance and available network bandwidth. and the output is the RED parameter. Simulation results demonstrate, even in low available bandwidth and asymmetrical bandwidth situations, the proposed approach effectively improve the delay and jitter of VoIP service packets. This work benefits network managers to enhance VoIP service by properly deploying RED queueing mechanism.
摘要  I
ABSTRACT  II
誌謝  III
論文目錄  IV
圖目錄  VI
表目錄  VIII
1.  緒論  1
1.1.  研究背景  1
1.2.  研究動機  4
1.3.  基本想法與解題方法  4
1.4.  預計成效及可應用對象  5
1.5.  文章組織  5
2.  VOIP的原理、協定及文獻探討  7
2.1.  VOIP的定義與基本交換技術  7
2.2.  VOIP的相關控制協定  11
2.2.1.  H.323協定  11
2.2.2.  SIP(Session Initiation Protocol)協定  12
2.2.3.  MGCP/MEGACO協定  15
2.2.4.  其它重要協定及技術  16
2.2.5.  各協定的優缺點比較  17
2.3.  被動式佇列管理機制  19
2.4.  主動式佇列管理機制  20
2.5.  KLAPEC方法  23
2.6.  JING LIU方法  23
3.  NEURAL NETWORK求解VOIP訊務之RED參數選擇  26
3.1.  腦細胞組織的探索與人工智慧概論與發展  26
3.2.  類神經網路起源及感知機的學習方法  29
3.3.  倒傳遞神經網路  36
3.4.  QUEUEMAX數值的決定方式  38
3.4.1.  類神經網路訓練及資料的編碼  38
3.4.2.  求出Queuemax的流程與方塊圖  41
4.  模擬與實驗結果  43
4.1.  架構說明與參數取得  43
4.2.  實驗環境圖  47
4.3.  模擬實驗分析  49
4.3.1.  單點傳輸模擬實驗  49
4.3.2.  100點傳輸實驗  50
4.3.3.  200點傳輸實驗  51
4.3.4.  不同佇列長度實驗  52
4.4.  封包的延遲與音訊品質  54
5.  結論  55
5.1.  本文貢獻  55
5.2.  未來展望  55
參考文獻  56
附錄一 訓練資料編碼  58
附錄二 BPN訓練後各層權重值  59
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