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采用自适应神经元的随机指数标记策略 被引量：2

Random exponential marking strategy based on adaptive neuron
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摘要 为了提高随机指数标记算法(REM)的响应能力和适应性,提出了一种基于自适应神经元的REM算法(ANREM)。采用具有比例积分微分(PID)控制属性的加强型价格来检测和控制网络拥塞。利用神经元构造PID价格,并设计控制参数的自适应调整机制,以增强算法在动态环境中的适应性。在NS2仿真平台中,将AN-REM与REM及其改进方法进行对比实验。结果表明,ANREM提高了队列长度的响应能力,增强了主动队列管理算法的适应性和鲁棒性。 To improve the responsiveness and adaptability of random exponential marking （REM） , this paper proposed a no- vel REM algorithm named ANREM based on adaptive neuron. ANREM employed an enhanced price with proportional-integral- derivative （PID） control property to detect and control network congestion. Introduced an adaptive neuron to design the PID- type price, in which adjusted the control parameters online to improve the adaptability in dynamic network scenarios. Conduc- ted simulation experiments in the NS2 platform to compare the performance of ANREM with those of REM and its variants. The results demonstrate that ANREM can enhance the responsiveness of queue length and improve the adaptability and robustness for active queue management.
作者 姚梦凯 黄文君 谭平
机构地区 浙江大学智能系统与控制研究所
出处 《计算机应用研究》 CSCD 北大核心 2011年第1期268-270,274,共4页 Application Research of Computers
基金 国家创新研究群体科学基金资助项目(60721062) 国家"863"计划资助项目(2007AA041301)
关键词 拥塞控制 主动队列管理 随机指数标记 自适应神经元 congestion control active queue management （AQM） random exponential marking （REM） adaptive neuron
分类号 TP393 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献13

  • 1BRADEN B, CLARK D, CROWCROFT J, et al.RFC 2309, Re-commendations on queue management and congestion avoidance in the Internet[S].[S.l.]: IETF, 1998.
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  • 4KUNNUYUR S S, SRIKANT R.An adaptive virtual queue (AVQ) algorithm for active queue management[J].IEEE/ACM Trans on Networking, 2004, 12(2): 286-299.
  • 5ATHURALIYA S, LI V H, LOW S, et al.REM: active queue ma-nagement[J].IEEE Network, 2001, 15(3): 48-53.
  • 6汪浩,牛玉刚.基于加强型价格的随机指数标记算法[J].华东理工大学学报（自然科学版）,2009,35(3):457-461. 被引量：2
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二级参考文献44

  • 1曾志民,张天魁,冯春燕,丁炜.一种快速响应的AQM算法[J].北京邮电大学学报,2005,28(4):5-9. 被引量：4
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  • 6Athuraliya S, Low S H, Li V H, et al. REM.. Active queue management [J]. IEEE Network, 2001, 15(3): 48-53.
  • 7Srisankar S Kunnuyur, Srikant R. An adaptive virtual queue (AVQ) algorithm for active queue management [J]. IEEE/ ACM Transactions on Networking, 2004, 12(2)..286-299.
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共引文献4

同被引文献20

  • 1刘明,张鹤颖,窦文华.随机指数标记算法的性能分析与控制模型[J].计算机工程与科学,2005,27(9):66-68. 被引量：4
  • 2FLOYD S, JACOBSON V. Random early detection gateways for congestion avoidance [J]. IEEE/ACM Transactions on Networking, 1993, 1(4): 397-413.
  • 3HOLLOT C V, MISRA V, TOWSLEY D, et al. On designing improved controllers for AQM routers supporting TCP flows [ C]//Proceedings of the Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies. Piseataway: IEEE Press, 2001:1726 - 1734.
  • 4ATHURALIYA S, LOW S H, LI V H, et al. REM: Active queue management [J]. IEEE Network Magazine, 2001, 15(3) : 48 - 53.
  • 5KUNNIYUR S, SRIKANT R. An Adaptive Virtual Queue (AVQ) algorithm for active queue management [ J]. IEEE/ACM Transactions on Networking, 2004, 12(2): 286-299.
  • 6WANG JUN, SONG MIN, YANG HOUJUN. Rate-based active queue management for congestion control over wired and wireless links [ C]// First International Conference on Communications and Networking. Washington, DC: IEEE Computer Society, 2006: 1- 6.
  • 7SUN JINSHENG, ZUKERMAN M. RaQ: A robust active queue management scheme based on rate and queue length [ J]. Computer Communications, 2007, 30(8) : 1731 - 1741.
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  • 10Lin X J;Shroff N B;Srikant R.On the Connection Level Stability of Congestion-Controlled Communication Networks,2008(05).

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计算机应用研究
2011年 第1期

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