数据包队列管理算法的设计。
摘要：分析了几种主动队列管理算法。
Absrtact: Analyze some major active queue management (AQM) algorithm.
是一种面向数据流的活动队列管理算法。
An active queue management algorithm for flows called MBUE is proposed.
研究了自适应的主动队列管理算法的设计。
The methods to design an adaptive AQM schemes are researched.
同时，本文还介绍几个具有代表性的经典的队列管理算法。
At the same time, this paper also introduces several classical queue management schemes.
提出了能有效预防网络拥塞，减少丢包率的数据包队列管理算法。
Offering the data packet queue management arithmetic to prevent the network congestion.
拥塞控制算法由TCP源算法和IP链路主动队列管理算法构成。
Congestion control algorithms are composed of TCP source algorithm and IP link active queue management algorithm.
PI算法是基于控制论的主动队列管理算法，具有队列长度抖动小的特点。
PI is the AQM algorithm cased on control theory and has smaller queue length oscillation than RED.
主动队列管理算法中，随机早期检测(RED)提供网络拥塞避免和拥塞控制机制。
In Internet, active queue management algorithm of random early detection (RED) algorithm provides congestion avoidance and control mechanisms.
主要取得了下列研究成果：(1)端到端拥塞控制中的主动队列管理算法和源算法的研究。
We have gotten following achievements. (1) Active queue management and source algorithms in end-to-end congestion control.
主动队列管理是目前的研究热点，随机早期检测(RED)算法是一种经典的队列管理算法。
Active queue management is a focus of current research. Random Early Detection (RED) is one kind of classical queue management algorithms.
针对网络存在较大时滞和网络参数动态变化等问题，提出了一种鲁棒非线性PI主动队列管理算法。
A robust nonlinear proportional integral (RNPI) algorithm for active queue management is proposed to alleviate the time-delay and parameters time-varying problems in network.
主动队列管理算法提供因特网中网络拥塞规避和控制机制，是因特网中分组转发设备的重要功能模块。
In the Internet, active queue management algorithm provides congestion avoidance and control mechanisms for Internet traffic as an important module in packet-forwarding devices.
针对具有输入时滞的TCP网络的拥塞控制问题，提出了一种基于自适应滑模控制的主动队列管理算法。
For the problem of congestion control in TCP networks with input-delay, an active queue management algorithm is presented based on an adaptive sliding mode control.
针对网络拥塞问题，提出一种基于模糊滑模控制的主动队列管理算法，能得到快速反应能力和良好的鲁棒性。
To solve the problem of congestion in internet, a fuzzy sliding mode control algorithm is proposed for the queue management.
随机早期检测（RED）队列管理算法的参数设置主要依赖于使用者的经验，并且其相关理论指导存在一定缺陷。
The parameter setting for Random Early Detection(RED) queue management algorithm depends on the user's experience and its related theoretical guidance exists some defects at present.
本文的平台实现部分详细讲述了队列管理框架和两种队列管理算法的设计和实现，并对相关技术进行了深入分析。
In the implementation part of this article, we present detailed design and implementation description of the framework and queue management schemes, as well as relative issues.
针对具有输入时滞和状态时滞的TCP网络的拥塞控制问题，提出了一种基于自适应滑模控制的主动队列管理算法。
For the problem of congestion control in TCP networks with input-delay and state-delay, an active queue management algorithm is presented based on an adaptive sliding mode control.
针对网络模型的不确定性和参数的时变性，该文提出了一种基于输入速率和队列长度变化的模糊控制主动队列管理算法。
Considering the uncertainty of network model and time variability of network parameters, a fuzzy control active queue management algorithm based on input rate and queue variance is proposed.
为了进行仿真实验，在NS2仿真器基础上扩展了PID主动队列管理算法，以此也展示了扩展ns2仿真器功能的一般性原理。
To carry out the experimental simulation, the function of NS2 is extended to support PID algorithm and meanwhile the general principle of the function extension of NS2 is shown.
在保留主动队列管理算法RED算法优点的基础上，引入了时间相关判定因子，算法有效地丢弃时间相关的数据，减少冗余信息。
Rest on retaining the advantage of the red algorithm and introducing time relevance determination factor, this algorithm is effective to discard time-related data and reduce redundant information.
与已有的几种主动队列管理算法的性能比较表明，PRED算法的性能明显优于ARED，PI控制，DRED，SRED和REM几种算法。
The performance comparisons with some active queue management algorithms show that the performance of PRED is obviously better than that of ARED, PI Controller, DRED, SRED and REM etc.
这让队列管理器能够使用常规的工作负载管理算法找到第二个储存库。
This enables the queue manager to find the second repository using normal cluster workload management algorithms.
这让队列管理器能够使用常规的工作负载管理算法找到第二个储存库。
This enables the queue manager to find the second repository using normal cluster workload management algorithms.
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