.png){kind=icon}
返回
Random Early Detection method for ABR service
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compeleceng.2007.03.005.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A new implementation for the Random Early Detection method algorithm for ABR (REDM-ABR) service is proposed in this paper. It keeps running all exponential average of the queue length (Q). When a cell arrives. the average queue size (Q(avg)) is compared with two threshold levels, lower queue threshold (Q(L)) and higher queue threshold (Q(H)). If it is smaller than Q(L), the cell is passed, but if it is larger than Q(H), the cell marking probability is set to one. If it is in between the two thresholds, the cell marking probability is calculated depending oil the value of Q(avg). The Values of Resource Management (RM) cell fields: Congestion Indication (CI), No Additive Increase (NI), and Explicit Rate (ER) are filled by the Relative Rate Marking (RRM) switch and sent back to the sources. The sources will change their rate depending on CI, NI, and ER values. To investigate the effect of decreasing the impending congestion area, a dynamic Q threshold (Q(D)) is used. The Q(D) is shifted from Q(L) toward Q(H) for decreasing the congestion area and to investigate the effect of this shift on the performance of the switch through simulation study. (C) 2007 Elsevier Ltd. All rights reserved.
Keyword:
Available Bit Rate (ABR)
Random Early Detection (RED)
Relative Rate Marking switch (RRM)
Backward Resource Management (BRM)
congestion increase
No Increase (NI)
Explicit Rate (ER)
Quality of Service (QoS)
Peak Cell Rate (PCR)
Minimum Cell Rate (MCR)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.9
论文数:
6.7K
被引数:
1.3W
机构
引用论文
.png){kind=icon}
没有更多内容
没有更多内容