层次网络中基于跳数区分的任意汇聚算法

从服务质量的实现来看,任意汇聚具有良好的延迟性能和扩展性,层次网络是有规则的网络拓扑,相比平面网络为任意汇聚的方法提供了更多的优势条件.通过建立任意汇聚的数学模型,分析了在层次网络体系结构中在一定的网络利用率条件下任意汇聚的最坏延迟约束,提出了一种基于跳数区分的任意汇聚调度算法.最后进行了实验分析,结果表明该方法能有效的改善任意汇聚的最坏延迟性能.     

一种基-于周期合并策略的流调度算法

在视频点播系统中.流调度算法通过降低服务延迟和提高服务效率等措施,可显著提高系统服务能力.提出了一种新的流调度算法--PeriodPatch.该算法在Patching算法的基础上引入了周期调度的规则.Period-Patch算法可以通过少数有序生成的组播节目流提供大量TVOD(truevideo_on_demand)级服务.PeriodPatch算法还保证系统在资源耗尽的情况下,可以提供高效、可预测的NVOD(nearvideo_on_demand)级服务.仿真结果表明,PeriodParch算法在TVO     

多服务级别带宽公平分配算法的研究

区分服务网络节点中的多级别的队列输出带宽由权值调度算法保证,固定权值调度在网络负载发生变化时无法继续提供公平的带宽保证。本文提出了一种动态调整权值的调度算法以达到在多服务级别间公平分配带宽。实验仿真表明,该算法可以对负载流数目的变化作出有效的响应,并快速实现调度权值的理想公平值。     

虚拟延迟矢量核心无状态调度策略VCSVC

提出一种新的核心无状态调度策略VCSVC（Vector Core Stateless Virtual Clock），可实现与VC相同的延迟特性，并提供逐点精确的基本（预留）带宽保证．后者是现有的核心无状态调度算法所不能保证的，为实现核心无状态下的公平调度策略提供了可能．VCSVC中，在边界节点计算的虚拟延迟矢量作为流状态带在分组头中，是核心节点排序的依据,核心节点的处理开销主要是排序操作，具有较高的可扩展性,为了限制虚拟延迟矢量编码长度，本文提出距离粒度法，证明了由此带来的误差对延迟特性无影响，对带宽分配的精确性影响不大．     

基于区分服务的队列调度算法研究

文中分析了在区分服务(DiffServ)模型下的WRR和DWRR调度算法的优缺点,提出了一种DWRR的改进调度算法DWRR+.该算法根据当前队列中分组的长度动态设置一次服务中发送分组的最大字节数,既保证了低权值业务的延迟特性,又保证带宽分配相对的公平性,避免了低优先级队列可能长时间得不到服务的缺点,改善了DWRR算法不能很好满足业务的时延特性.使用NS-2网络仿真器进行算法性能评价,仿真结果表明DWRR+算法在保证输出带宽的前提下降低了延时,可以在一定程度上保证不同业务的服务质量.     

一种区分服务域内的IP流量规划方法

IP流量规划与区分服务结合是增强网络服务质量保证的新方法.在分析区分服务对流量规划需求的基础上,设计了区分服务与流量规划结合的功能框架,提出了适合流量规划要求的队列调度方法和流量分割与映射的原理与方法.流分割方法基于表对数据流进行分割.该方法既能体现区分服务数据包的转发优先级的差异,又能保证数据流的延迟与同步要求.     

基于DiffServ的高效调度算法的研究

区分服务(DiffServ)体系是未来IP QoS研究的主要发展方向,在区分服务的体系下,队列调度是实现IP QoS的核心技术。在深入研究区分服务体系下的基本分组调度算法优缺点的基础上,提出一种改进算法,以队列分组的延迟特性,保证实时业务的实时特性。对改进算法进行了仿真,在多约束下,对性能进行了评价。     

DiffServ 中基于优先级的队列调度算法

为了提高 DWRR 算法的时延性能及应对突发流的能力,文中结合比例时延区分服务模型,在 DWRR 算法的基础上提出了一种能够体现优先级的队列调度算法-PDDRR.该算法的控制目标是保证各业务流的平均排队时延在无突发业务流时维持在给定的比率,而在应对突发流时忽略时延的比例公平原则,根据网络实时负载动态地调整各队列的权值,合理地分配资源.仿真结果表明,算法不仅能实现不同优先级业务的时延区分,而且在业务流突发时为各等级业务提供服务质量保证.     

一种可提供绝对服务质量分级的优先调度算法

提出了一种能够提供端到端时延保证和满足丢包率要求的多优先级算法。该算法以分组头中记录的时延、丢包率、保证带宽为权重对分组进行调度,通过对信元的相对优先级及服务质量参数的加权算法,得到一种公平的满足绝对服务质量的算法。还能够使系统避免维护每个流的状态信息以及对单个流进行复杂的队列管理和调度,由此增加了系统的可扩展性。计算机仿真表明该算法具有较高的资源利用率,较低的端到端时延和时延抖动以及较低的分组丢弃率等特点。     

一种在MPLS网络中提供单流QoS保障的区分服务标记方法*

为了在MPLS网络中提供对单流的高质量服务,提出了一种基于网络的、供应方的区分服务标记方法。在数据流进入网络前按交换路径进行逐点的接入控制,再将许可的资源预留作为流状态安装在入口路由器上。在传输时,数据流在入口路由器按资源预留标记为预留内/预留外,网络节点按不同的标记队列进行区分处理。该方法提出按预留带宽标记数据流,将基于单流的资源预留定量地映射为基于行为聚合的PHB标记,实现了从集成服务到区分服务的融合。其一方面避免了拥塞,提供了对单流的定量服务质量保证;另一方面无须在核心路由器安装流状态和实现流管理,保持了区分服务的可扩展性。     

A robust packet scheduling algorithm for proportional delay differentiation services

Proportional delay differentiation (PDD) model is an important approach to relative differentiated services provisioning on the Internet. It aims to maintain pre-specified packet queueing-delay ratios between different classes of traffic at each hop. Existing PDD packet scheduling algorithms are able to achieve the goal in long time-scales when the system is highly utilized. This paper presents a new PDD scheduling algorithm, called Little’s average delay (LAD), based on a proof of Little’s Law. It monitors the arrival rate of the packets in each traffic class and the cumulative delays of the packets and schedules the packet according to their transient queueing properties in order to achieve the desired class delay ratios in both short and long time-scales. Simulation results show that LAD is able to provide predictable and controllable services in various system conditions and that such services, whenever feasible, can be guaranteed, independent of the distributions of packet arrivals and sizes. In comparison with other PDD scheduling algorithms, LAD can provide the same level of service quality in long time-scales and more accurate and robust control over the delay ratio in short time-scales. In particular, LAD outperforms its main competitors significantly when the desired delay ratio is large.     

Fundamental trade-offs in aggregate packet scheduling

In this paper, we investigate the fundamental trade-offs in aggregate packet scheduling for support of guaranteed delay service. In our study, we consider two classes of aggregate packet scheduling algorithms: the static earliest time first (SETF) and dynamic earliest time first (DETF). Through these two classes of aggregate packet scheduling (and together with the simple FIFO packet scheduling algorithm), we show that, with additional timestamp information encoded in the packet header for scheduling purposes, we can significantly increase the maximum allowable network utilization level, while, at the same time, reducing the worst-case edge-to-edge delay bound. Furthermore, we demonstrate how the number of the bits used to encode the timestamp information affects the trade-off between the maximum allowable network utilization level and the worst-case edge-to-edge delay bound. In addition, the more complex DETF algorithms have far superior performance than the simpler SETF algorithms. These results illustrate the fundamental trade-offs in aggregate packet scheduling algorithms and shed light on their provisioning power in support of guaranteed delay service.     

基于多跳间时延协作的最久分组优先算法

提出了一种基于多跳间时延协作的Crossbar调度算法。该算法以分组头中记录的时延为权重对分组进行调度，通过控制分组在各跳上的时延来达到调节端到端时延的目的。算法还使路由器避免了维护每个流的状态信息以及对单个流进行的复杂的队列管理和调度。计算机仿真表明，算法具有较高的资源利用率、较低的端到端时延抖动和较低的分组丢弃率等特点。     

The service curve service discipline for the rate-controlled EDF service discipline in variable-sized packet networks

Guaranteed service will provide high quality services to real-time applications, e.g., audio or video, over packet networks such as the Internet. To support guaranteed service, a service discipline must guarantee a delay bound to each session. In addition, a preferred service discipline should achieve high network utilization and good scalability. The service disciplines studied so far have problems in achieving these two objectives at the same time. Generalized processor sharing (GPS) service disciplines can have low network utilization. Rate-controlled (RC) service disciplines have difficulty in scalability because of regulators. For service curve (SC) service disciplines, both the network utilization and the scalability depend on the adopted SC. To date, there have been no studies on an SC which can make an SC discipline achieve these two objectives. We propose a new service discipline based on SC service disciplines. The proposed discipline achieves these two goals in a variable-sized packet environment. We show that the discipline can achieve the network utilization achievable by the RC service disciplines. We further show that our SC requires O(1) complexity for deadline calculation. Different from the RC service disciplines, the SC service discipline with our SC does not need regulators at all. Thus, it has better scalability than the RC service disciplines and is work-conserving. We also show that the proposed SC makes SC service disciplines have strictly higher network utilization than the GPS service disciplines including the multi-rate service discipline.     

A proportional fairness scheduling for wireless sensor networks

This paper describes a packet scheduling algorithm for wireless sensor networks (WSNs) that meets the proportional fairness principle. Based on the weighted round-robin strategy, the proposed scheduling algorithm allocates a different service quota to different traffic according to the average packet arrival rate. This guarantees proportional fairness in terms of the average packet delivery delay and the average packet loss ratio. Since the scheduling algorithm does not perform high-load operations such as time stamping and sorting, it can be implemented easily and is suitable for resource-limited WSNs. The proposed scheduling algorithm is tested in a WSN and is found to guarantee the proportional fairness of the average packet delivery delay when this is used as the performance metric, and to realize proportional fairness in the average packet loss ratio when all the queues are overflowing and the average packet loss ratio is used as the performance metric.     

包交换网络中调度方法进展：扩展性分析

1.引言现在Internet主要提供无服务质量(QoS)保证的尽力服务(best effort)。随着Internet朝着提供包括数据、声音、视频等多服务统一的多媒体通讯平台发展,传统的Internet已经不能满足不同的应用在吞吐率、延迟、延迟抖动、丢失率等方面的不同要求。服务质量控制作为网络提供保证服务的手段在近十多年的时间里得到了广泛的研究。传统的服务质量研究主要基于集成服务(Intserv/RSVP)模型。这种模型的基本思想是为每一个流提供端到端的服务质量控制,它的实     

一种动态优先级排序的虚拟机I/O调度算法

I/O任务调度是影响I/O密集型虚拟机性能的重要因素。现有调度方法主要是针对虚拟机整机I/O带宽的优化,较少兼顾各虚拟域与全局性能,也无法满足域间差异化服务的要求。针对现有方法的不足,提出了一种动态优先级排序的虚拟机I/O调度算法DPS。该算法基于多属性决策理论,以离差最大化方法计算I/O任务的优先级评估属性权重,对I/O任务优先级进行综合评估;通过引入任务所在虚拟域价值,体现云计算环境下虚拟域重要性差异。在Xen系统中通过实验评测DPS调度虚拟化网卡的性能,结果表明,DPS能够有效提高指定域与全局的I/O任务截止期保证率、整机I/O带宽,并能为不同虚拟域的I/O应用提供差异化服务。     

MHWSN中保证混合业务QoS的跨层调度算法

针对中高速传感器网络中混合业务QoS（Quality of Service）要求,跨层考虑物理层和数据链路层参数,提出了一种保证混合业务服务质量的调度算法AM-LWDF。该算法同时考虑时延优先级和吞吐量优先级,在满足实时业务QoS约束的前提下,以最大化系统吞吐量为目标建立了相应的优化模型,对实时业务能够满足时延较小的要求,对非实时业务满足吞吐量较大的要求。仿真结果表明,该调度算法可以灵活地在时延和吞吐量之间取得满意的折衷,并保证不同类型业务用户间的公平性。     

IEEE802.16e的实时上行链路调度服务优化算法

深入分析了IEEE802.16e建议的三种实时调度服务算法：UGS、rtPS、ertPS，并在此基础上提出了一种优化的实时调度服务算法：irtPS。该优化的调度服务算法在保证变化数据率实时上行链路的延时性能基础上，最大限度地提高了实时上行链路的资源利用率。数学建模分析结果显示，在保证延时性能的前提下，该优化的调度服务算法的系统容量较IEEE802.16e建议算法的系统容量有显著增加。     

Scheduling and admission control for integrated-services networks: the Priority Token Bank

This paper proposes a new mechanism called the Priority Token Bank for admission control, scheduling and policing in integrated-services networks. In such networks, both arrival processes and performance objectives can vary greatly from one packet stream to another. There are two principal components to the Priority Token Bank: accepting or rejecting requests to admit entire packet streams, where acceptance means guaranteeing that the packet stream's performance objectives will be met, and scheduling the transmission of packets such that performance objectives are met, even under heavy loads. To the extent possible, the performance of traffic is also optimized beyond the requirements. The performance achieved with the Priority Token Bank is compared to that of other typical algorithms. It is shown that, when operating under the constraint that the performance objectives of applications such as packet voice, video and bulk data transfer must be met in an ATM network, the mean delay experienced by other traffic is much better with the Priority Token Bank. Furthermore, the admission control algorithm can guarantee requirements will be met, and admit more traffic than the common alternatives.