核心无状态队列管理算法的公平性研究

研究了以CSFQ为主要代表的核心路由器中无状态公平排队技术,在该算法的基础上,针对其实际实现公平性方面的不足,提出了一种改进的MCSFQ算法。在链路产生拥塞时,新算法根据队列长度的变化情况,对公平共享速率进行不同程度的调整,使公平共享速率的取值更加合理。仿真实验证明,该算法在保持了CSFQ算法优点的基础上,进一步改善了在不同数据流间带宽分配的公平性。     

一种采用公平策略的CSFQ算法

研究一种对核心无状态公平队列调度(CSFQ)算法的改进方法.针对CSFQ缓存资源管理的弊病,造成路由器突发性流响应差及对响应流TCP和非响应流UDP不公平的问题,提出了一种公平策略的CSFQ算法(FCSFQ).FCSFQ提出了基于共享存储器模式的动态缓存管理机制,并以此来改善CSFQ突发性响应差问题,同时采用对响应流与非响应流不同的丢包策略,来解决CSFQ对不同数据流不公平问题.NS仿真实验表明,在现实网络环境下,FCSFQ算法对突发性响应及带宽在TCP、UDP数据流之间的公平分配都有明显改善.     

高吞吐量的核心无状态公平队列算法

提出了一种优化的核心无状态公平队列凋度算法(xCSFQ),在CSFQ的基础上,根据缓冲区占用率和数据流到达速率决定丢包概率,缓存管理上采用基于CHOKC原理的机制进行缓存管理,解决了CSFQ链路利用率低的问题,提高了带宽在UDP流和TCP流之间分配的公平性,最后对算法进行了仿真分析。     

基于路由器的公平带宽分配算法研究

本文介绍了目前在路由器上存在的几种带宽分配的不公平性问题,阐述了在路由器上如何避免这种不公平性,并对核心无状态公平队列调度(CSFQ)算法进行详尽分析,指出了CSFQ算法的问题并总结了目前的解决方法以达到带宽分配的尽可能公平.     

一种基于公平性MPLS的流控制技术研究

多媒体业务在Internet上的广泛应用带来了响应流和非响应流间带宽享用的公平性问题,严重影响网络的性能.提出一种基于公平的MPLS流控制机制,该机制通过在MPLS模型中添加特定的队列管理算法CSFQ,在一定程度上解决了MPLS域中流间的公平性问题,并且其对于MPLS设备的扩展完全可以通过软件的升级来实现,有较好的可行性.     

应用Best-Effort思想的公平排队算法

研究了以CSFQ为主要代表的核心路由器中无状态公平排队技术，针对其在吞吐量等性能上的不足，提出了一种结合CSFQ与FIFO两种技术的公平排队算法CSFQ—β．算法能够达到近似公平的带宽分配，在保持了CSFQ的其它优点基础上．更进一步地改善了总体吞吐量．减少了包的转发时延，并更有效地利用了链路带宽，且仍能避免拥塞的产生．     

CSFQ算法分析与改进

核心无状态公平队列调度（CSVQ）算法提供了如同有状态网那样好的公平带宽分配,但它的丢包算法不适用于TCP流。针对TCP流的特点,对CSFQ算法进行如下改进：将缓存队列长度与丢包概率关联起来,用一种类似于RED（random early drop）缓存管理方法解决了缓存频繁溢出导致的一些问题;对TCP流的丢包率进行修正,使用多余带宽来转发TCP包,解决TCP流与UDP流的带宽分配公平性。仿真试验表明,新算法NEW-CSFQ更好地提供数据流公平的频宽共享,对突发流响应较原算法有所提高,且算法复杂度简单,容易在高速核心路由器上实现。     

一种在区分服务网络中新的三色标记器

研究了在区分服务体系结构中传统的标记算法,传统的标记算法不能提供标记的准确性和按比例共享带宽的公平性.在此基础上,提出了一种改进的标记算法.该算法在进行数据包的标记时,同时考虑平均速率和瞬时速率两个参数,提高了标记的准确性.当流的速率超过目标速率时,按照正比于数据流的速率的概率将超过速率的流标记为黄色,这样提高了对剩余带宽的公平共享性.试验证明,ITCM算法与传统的标记算法相比,不仅能提高吞吐量,还可以达到剩余带宽的按比例共享.     

自适应带宽的最大-最小公平性拥塞控制

带宽共享和拥塞控制对于Internet的健壮性和公平性是很重要的研究课题.对交换设备中流量共享拥塞链路的带宽公平分配进行研究,提出一个优化交换设备带宽的设置算法:根据出端口接收速率自适应设置入端口带宽门限,对入端口的带宽进行动态重新分配,提高资源利用率.模拟实验表明,此算法有以下优点:1)高适应性;2)最大最小公平性;3)快速响应网络变化;4)高可靠性;5)稳定性.     

基于改进樽海鞘算法的共享单车分布密度优化

针对城市共享单车分布密度优化问题,提出了一种改进樽海鞘算法.首先,将共享单车分布密度优化问题转换成函数优化问题,以等待时间、花费时间、费用及安全代价为评价指标,建立目标函数.其次,引入一维正态云模型和非线性递减控制策略来改进樽海鞘算法中引领者的搜索机制,增强对局部数据的挖掘能力;引入自适应策略来改进原算法跟随者搜索机制,避免算法陷入局部最优值.最后,通过标准测试函数以及共享单车分布密度优化仿真对所提优化算法的有效性进行了验证,结果表明:相比原樽海鞘算法、萤火虫算法及人工蜂群算法,改进的樽海鞘算法具有更好的稳定性和全局搜索能力,能够更好地实现对共享单车分布密度的优化,提升共享单车的区域利用率,对智慧交通的发展有一定的参考价值.     

一种基于速率的公平队列管理算法

针对主动队列管理算法普遍存在的公平性问题,提出基于速率的公平队列管理算法RFED。该算法根据分组的到达速率调节丢包率,将队列的到达速率控制在链路的服务速率下,根据非响应流UDP数据包空间分布特点,对非响应流实施有效的惩罚,以保证不同数据流之间的公平。NS仿真实验表明,该算法在公平性、稳定性等方面效果良好,无需进行复杂的参数配置,容易在现有网络中实施。     

基于ECN的单播流与多播流间带宽共享算法

An ECN-based implementing bandwidth-sharing algorithm for unicast and multicast flows is presented.The algorithm uses a bandwidth allocation strategy to give an incentive to multicast flows in bandwidth allocation according to algorithm of the number of receivers, and to assure the unicast flows get their bandwidth shares fairly.Provided best-effort networks, an ECN-based congestion control algorithm is used to implement differentiated service in bandwidth allocation between unicast flows and multicast flows. In implementation, we solve the problems such asreceiver‘s number estimation, the RTT estimation and compromise between convergence and stability.The simulation results show that the algorithm can implement bandwidth sharing for TCP flows and multicast flows. Atthe same time, the algorithm not only allocates more bandwidth to multicast flows, but promises TCP flows to get their fair bandwidth share.     

一种短流优先的公平带宽分配机制

提出一种短流优先的公平带宽分配机制FPIP(fair PIP).通过区别处理短流和长流的报文,FPIP能够将带宽优先分配给短流,然后将剩余的带宽在长流之间公平分配.此外,FPIP采用主动队列管理机制AQM(active queue management)检测拥塞并控制队列长度.仿真结果表明,FPIP在保证公平性、控制队列长度、减小Web流的响应时间等方面具有良好的性能.     

Fair Scheduling Algorithms in Grids

In this paper, we propose a new algorithm for fair scheduling, and we compare it to other scheduling schemes such as the earliest deadline first (EDF) and the first come first served (FCFS) schemes. Our algorithm uses a max-min fair sharing approach for providing fair access to users. When there is no shortage of resources, the algorithm assigns to each task enough computational power for it to finish within its deadline. When there is congestion, the main idea is to fairly reduce the CPU rates assigned to the tasks so that the share of resources that each user gets is proportional to the users weight. The weight of a user may be defined as the users contribution to the infrastructure or the price he is willing to pay for services or any other socioeconomic consideration. In our algorithms, all tasks whose requirements are lower than their fair share CPU rate are served at their demanded CPU rates. However, the CPU rates of tasks whose requirements are larger than their fair share CPU rate are reduced to fit the total available computational capacity in a fair manner. Three different versions of fair scheduling are adopted in this paper: the simple fair task order (SFTO), which schedules the tasks according to their respective fair completion times, the adjusted fair task order (AFTO), which refines the SFTO policy by ordering the tasks using the adjusted fair completion time, and the max-min fair share (MMFS) scheduling policy, which simultaneously addresses the problem of finding a fair task order and assigning a processor to each task based on a max-min fair sharing policy. Experimental results and comparisons with traditional scheduling schemes such as the EDF and the FCFS are presented using three different error criteria. Validation of the simulations using real experiments of tasks generated from 3D image- rendering processes is also provided. The three proposed scheduling schemes can be integrated into existing grid computing architectures.     

一种ATM网络拥塞控制算法的仿真研究

该文讨论了一种基于随机控制理论的ATM网络拥塞控制算法,将该算法应用于带宽变化状态下ABR的拥塞控制问题研究。仿真结果表明：对于带宽变化的情况,该算法对交换机处排队长度有很好的控制效果,并且有很高的带宽资源利用率,同时能在各VCS间实现速率的公平分享。同时将该算法和ATM论坛的ERICA 算法进行了仿真和比较,仿真结果证明：采用该算法使得交换机队列长度、源速率、交换机输出能力波动平缓。该算法在控制队列长度及震荡、提高带宽的利用率以及实现速率公平性原则方面优于ERICA 算法。     

Smith's principle for congestion control in high-speed datanetworks

In high-speed communication networks, large propagation delays could have an adverse impact on the stability of feedback control algorithms. In this paper, the classical control theory and Smith's principle are exploited to design an algorithm for controlling “best effort” traffic in high-speed asynchronous transfer mode (ATM) networks. The designed algorithm guarantees the stability of network queues, along with the fair and full utilization of network links, in a realistic traffic scenario in which multiple available bit rate connections, with different propagation delays, share the network with high priority traffic     

Identification of spatiotemporally invariant systems for control adaptation

We present a distributed projection algorithm for system identification of spatiotemporally invariant systems with the ultimate purpose of utilizing it in an indirect adaptive control scheme. Each subsystem communicates only with its immediate neighbors to share its current estimate along with a cumulative improvement index. On the basis of the cumulative improvement index, the best estimate available is picked in order to carry out the next iteration. For small estimation error, the scheme switches over to a “smart” averaging routine. The proposed algorithm guarantees to bring the local estimates arbitrarily close to one another, developing a “local consensus”, which makes it amenable to control by the application of indirect distributed adaptive control schemes. It is also shown through simulations that the proposed algorithm has a clear advantage over the standard projection algorithm. Our proposed algorithm is also suitable for addressing the estimation problem in distributed networks that arise in a variety of applications, such as environment monitoring, target localization and potential sensor network problems.