最新-Fundamental QoS Routing Experiment基本的QS路由实验-PPT文档资料

合集下载

QOS 基础精讲

QOS 基础精讲

QOS 基础2017年10月26日22:02QOS是一种基本的网络架构技术,他与高可靠性(high-availability)技术及安全技术(security)属于同一类型。

QOS不仅能为终端用户提供不同级别的服务,还可以实现一些安全方面与业务方面的需要。

几种重要的流量特征∙延迟(时延):指数据包从发送方发出,直至其到达接收方,所经历的时间之和。

∙抖动(时延变量):是指多个数据包之间,端到端延迟的差异或变化。

∙丢包率:用成功收发的数据包数,除以发送的数据包总数,所得到的百分比。

几种主要流量的大体特征∙语音:平滑|温和|对丢包敏感|对时延敏感|UDP最佳优先级单向要求:时延<=150ms|抖动<=30ms|丢包率<=1%|带宽(30~128kbit/s)∙视频:突发|排他|对丢包敏感|对时延敏感|UDP最佳优先级单向要求:时延<=200~400ms|抖动<=30~50ms|丢包率<=0.1%~1%|带宽(384kbit/s~20+Mbit/s)4K点播需求25-40M,直播需求带宽18-30M。

建议大于50M∙数据:平滑/突发|温和/排他|对丢包不敏感|对延迟不敏感|TCP重传1、QOS 模型∙Best-effort service:尽力而为服务尽力而为服务模型,其实没有实施任何QOS,默认的网络都工作在这种模型下∙Integrated service:集成服务(RFC1633、RFC211和RFC2212)在实施了intserv服务模型QOS的网络中,应用程序在发送数据之前,必须先向网络申请带宽(使用RSVP协议)。

当网络同意后,保证能够得到所申请的带宽,而不会有任何延迟。

但是如果某些程序在连接之前没有向网络申请带宽,那么它的流量只能得到尽力而为的服务。

∙Differentiated service:差分服务(RFC2472、RFC2597、RFC2598、RFC3246、RFC4594)在实施了diffserv服务模型QOS的网络中,网络根据不同数据提供不同服务,因此所有数据都被划分为不同的类别,或者设置为不同的优先级。

IP QoS

IP QoS

路由器系统部
10
单中继段行为 - PHB
PHB(Per-Hop Behaviors) ( )
PHB是网络节点对报文调度、丢包、监管和整形的处理, 是网络节点对报文调度、丢包、监管和整形的处理, 是网络节点对报文调度 每类PHB都对应一组 都对应一组DSCP;PHB只定义了一些外部可见 每类 都对应一组 ; 只定义了一些外部可见 的转发行为, 的转发行为,没有指定特定的实现方式
LSP setup
IGP route selection Link-state database
LSP path selection Traffic-engineering database
Signaling component
Information flooding Packets in
IS-IS/OSPF routing Packet-forwarding component Packets out
SPD 链路层
物理层
LFI LR
接收报文
发送报文
路由器系统部
SNMP
21
CAR&ISPKeeper
基本IP QoS技术 基本IP QoS技术
流量调节器
包括CAR、GTS 、ISPKeeper、BAS等
标记
包括优先级、DSCP、MPLS EXP等
拥塞避免和管理
拥塞避免策略包括尾丢弃、RED、WRED等,拥塞管理方法 包括FIFO、PQ、CQ、WFQ、RTP实时队列、CBWFQ/LLQ等
路由器系统部
14
MPLS 流量工程隧道
MPLS TE隧道 隧道
用户设备 运营商网络 LSR LER 用户设备
LER
拥塞链路 MPLS TE隧道

环形网络的QoS保证机制

环形网络的QoS保证机制

环形网络的QoS 保证机制环形网络的QoS保证机制环形网络是一种常见的网络拓扑结构,它由一系列节点以环形的方式连接起来。

在环形网络中,每个节点都与其相邻的节点直接相连,数据可以在环形路径上进行传输。

然而,由于环形网络的特殊结构,QoS(Quality of Service)保证成为了一个重要的问题。

QoS保证机制可以确保网络在传输数据时满足一定的服务质量要求,例如低延迟、高带宽等。

在环形网络中,QoS保证机制可以通过以下步骤来实现:第一步,定义QoS目标:确定所需的服务质量目标,例如最大延迟、最小带宽等。

这些目标将指导后续的QoS保证机制设计。

第二步,流量管理:在环形网络中,流量管理是实现QoS保证的关键。

通过合理的流量管理,可以控制网络流量的传输速度和优先级,以确保满足QoS目标。

第三步,拥塞控制:拥塞是环形网络中常见的问题,当网络中的数据流量超过网络资源的处理能力时,就会发生拥塞。

拥塞会导致延迟增加、丢包率增加等问题,因此需要采取拥塞控制策略来保证QoS。

第四步,优先级调度:在环形网络中,不同的数据流可能有不同的QoS要求。

通过为不同的数据流分配不同的优先级,可以确保高优先级的数据流能够在网络中得到优先传输,从而满足其QoS要求。

第五步,错误处理:在环形网络中,可能会出现各种错误,例如数据丢失、错误的路由选择等。

为了保证QoS,需要采取相应的错误处理策略,例如重新传输数据、重新选择路由等,以确保数据能够正确地传输。

第六步,性能监测与调优:QoS保证机制的实施并不是一次性的过程,需要不断地监测网络性能并进行调优。

通过对网络性能的实时监测和分析,可以及时发现问题并采取相应的措施来提高网络的QoS。

综上所述,QoS保证机制在环形网络中是非常重要的。

通过合理的流量管理、拥塞控制、优先级调度、错误处理以及性能监测与调优等步骤,可以有效地实现对网络服务质量的保证。

只有确保QoS,才能满足用户对网络的要求,提高网络的可靠性和稳定性。

QoS队列调度算法

QoS队列调度算法

QoS队列调度算法队列指的是在缓存中对报⽂进⾏排序的逻辑。

当流量的速率超过接⼝带宽或超过为该流量设置的带宽时,报⽂就以队列的形式暂存在缓存中。

报⽂离开队列的时间、顺序,以及各个队列之间报⽂离开的相互关系由队列调度算法决定。

华为交换机设备的每个端⼝上都有 8 个下⾏队列,称为CQ(Class Queue)队列,也叫端⼝队列(Port-queue),在交换机内部与前⽂提到的 8 个PHB⼀⼀对应,分别为BE、 AF1、AF2、AF3、AF4、EF、CS6 和CS7。

单个队列的报⽂采⽤ FIFO(First In First Out)原则⼊队和出队。

PQ(Priority Queuing)调度PQ(Priority Queuing)调度,就是严格按照队列优先级的⾼低顺序进⾏调度。

只有⾼优先级队列中的报⽂全部调度完毕后,低优先级队列才有调度机会。

采⽤PQ 调度⽅式,将延迟敏感的关键业务放⼊⾼优先级队列,将⾮关键业务放⼊低优先级队列,从⽽确保关键业务被优先发送。

PQ调度的缺点是:拥塞发⽣时,如果较⾼优先级队列中长时间有分组存在,那么低优先级队列中的报⽂就会由于得不到服务⽽“饿死”。

假设端⼝有 3 个采⽤PQ调度的队列,分别为⾼优先(High)队列、中优先(Medium)队列、和低优先(Low)队列,它们的优先级依次降低。

如图,其中报⽂编号表⽰报⽂到达顺序。

图1 PQ调度RR(Round Robin)调度RR调度采⽤轮询的⽅式,对多个队列进⾏调度。

RR以环形的⽅式轮询多个队列。

如果轮询的队列不为空,则从该队列取⾛⼀个报⽂;如果该队列为空,则直接跳过该队列,调度器不等待。

图2 RR调度RR调度各个队列之间没有优先级之分,都能够有相等的概率得到调度。

RR调度的缺点是:所有队列⽆法体现优先级,对于延迟敏感的关键业务和⾮关键业务⽆法得到区别对待,使得关键业务⽆法及时得到处理WRR(Weighted Round Robin)调度加权轮询WRR(Weighted Round Robin)调度主要解决RR不能设置权重的不⾜。

新一代QoS研究_高等计算机网络课程汇报PPT

新一代QoS研究_高等计算机网络课程汇报PPT

2 网络QoS体系结构
IntServ体系结构是IETF 1994年提出的QoS 保证模式.它是在传统IP网络尽力而为服务模式 的基础上定义了一组服务扩充,通过RSVP提供端到 端的QoS保障.IntServ虽然能够提供较好QoS保证, 但其基于面向连接模式,而IP网络本身是非连接的, 因此高速网络核心路由器常常被迫去维护、调度 数以千计的连接.随着连接数量的增加,连接建立 和连接释放阶段的额外开销也会增大,每个连接 的状态信息需要保存在路径通过的每个节点上, 即需要保存每流状态,其可扩展性差.而且在具体 实施中,如何与现有IP网络互连也是一个困难.

2 网络QoS体系结构
基于此,我们提出了Peer-Server-Peer(PSP)的 新的IP QoS体系结构,控制信息路径和数据路径是 相互独立的.

2 网络QoS体系结构
现有互联网基本采用全分布式的自适应路由 策略.每个路由器既要实现分组转发的功能,又要 实现选路控制的功能,要实时地掌握全网的状态 (网络拓扑和各链路的流量),建立和维护网络拓 扑数据库,频繁地交换路由信息并达到同步;在此 基础上,进行路由计算,选择最好路径,更新路由表. 随着互联网规模的扩大,这种模式的脆弱性暴露得 愈来愈明显,导致互联网称为“一个复杂的不稳定 系统”。

目录
You can briefly add outline of this slide page in this text box.
1引言 2 网络QoS体系结构 3 实时QoS保证
4 融合QoP的QoS控制 5 结论

1引言
随着高速网络技术和多媒体技术的飞速发展, 人们越来越多地提出了包括多媒体通信在内的综 合服务要求.传统的分组交换网络,如Internet,是面 向非实时的数据通信而设计的,采用的TCP/IP协议 主要是为了优化整个网络的数据吞吐量并保证数 据通信的可靠性.而当今分布式多媒体应用(如视频 会议、视频点播、IP可视电话、远程教育)不仅 包括文本数据信息,还包括语音、图形、图像、 视频、动画这些类型的多媒体信息.分布式多媒体 应用不仅对网络有很高的带宽要求,

qos基本原理

qos基本原理

qos基本原理QoS大揭秘:网络服务质量的奥义与实战在当今这个数字化时代,信息如同湍急的洪流,穿越在光纤与电磁波之间。

而在这浩渺的数据海洋中,有一种力量犹如舵手,精准调控着数据传输的质量和效率,这便是我们今天要揭开神秘面纱的主角——QoS(Quality of Service),即网络服务质量。

想象一下,你正在家中舒适地享受一场高清无卡顿的在线电影盛宴,或者在游戏中畅快淋漓地与队友并肩作战,这一切的背后,都离不开QoS这位默默无闻的幕后英雄。

它就像一位公正无私的裁判员,确保每一比特数据都能按时按量、有序高效地送达目的地,从而保障了我们各类网络应用的流畅体验。

那么,QoS的基本原理究竟是什么呢?说来也简单,就如同繁忙的城市交通需要有合理的调度机制以保证道路畅通,QoS在网络世界中承担的就是这样的角色。

它通过对不同类型的网络流量进行分类、标记,并根据不同业务对带宽、时延、丢包率等关键性能指标的需求,实施差异化的服务策略,实现网络资源的合理分配。

举个例子,就仿佛VIP客户能享受银行快速通道一样,在网络中,实时性要求高的语音通话或视频会议这类“VIP”流量,就能通过QoS得到优先级更高的传输待遇,避免被普通文件传输等“普通客户”流量所阻塞。

这就是QoS中的优先级控制,也是其核心机制之一。

同时,QoS还采用流量整形、带宽限制、拥塞管理等多种手段,像一位灵活应对各种情况的智能管家,无论网络负载如何变化,都能确保重要业务不被打扰,有效防止网络拥塞的发生。

再者,QoS还能帮助我们在多用户共享网络资源的场景下,化解“僧多粥少”的尴尬局面。

比如在企业内部网中,员工们同时使用邮件系统、ERP系统以及进行远程视频会议,QoS就能根据预先设定的服务等级协议(SLA),合理调配有限的带宽资源,让每一个应用各得其所,实现和谐共生。

总之,QoS以其独特的策略和服务机制,构建了一套完善且动态适应的网络管理体系,使得宝贵的网络资源得以最大限度地发挥效用,满足不同用户、不同业务的多元化需求。

QoS技术详解及实例

QoS技术详解及实例

一般来说,基于存储转发机制的Internet(Ipv4标准)只为用户提供了“尽力而为(best-effort)”的服务,不能保证数据包传输的实时性、完整性以及到达的顺序性,不能保证服务的质量,所以主要应用在文件传送和电子邮件服务。

随着Internet的飞速发展,人们对于在Internet上传输分布式多媒体应用的需求越来越大,一般说来,用户对不同的分布式多媒体应用有着不同的服务质量要求,这就要求网络应能根据用户的要求分配和调度资源,因此,传统的所采用的“尽力而为”转发机制,已经不能满足用户的要求。

QoS的英文全称为"Quality of Service",中文名为"服务质量"。

QoS是网络的一种安全机制, 是用来解决网络延迟和阻塞等问题的一种技术。

对于网络业务,服务质量包括传输的带宽、传送的时延、数据的丢包率等。

在网络中可以通过保证传输的带宽、降低传送的时延、降低数据的丢包率以及时延抖动等措施来提高服务质量。

通常 QoS 提供以下三种服务模型:Best-Effort service(尽力而为服务模型)Integrated service(综合服务模型,简称Int-Serv)Differentiated service(区分服务模型,简称Diff-Serv)1. Best-Effort 服务模型Best-Effort 是一个单一的服务模型,也是最简单的服务模型。

对Best-Effort 服务模型,网络尽最大的可能性来发送报文。

但对时延、可靠性等性能不提供任何保证。

Best-Effort 服务模型是网络的缺省服务模型,通过FIFO 队列来实现。

它适用于绝大多数网络应用,如FTP、E-Mail等。

2. Int-Serv 服务模型Int-Serv 是一个综合服务模型,它可以满足多种QoS需求。

该模型使用资源预留协议(RSVP),RSVP 运行在从源端到目的端的每个设备上,可以监视每个流,以防止其消耗资源过多。

Qos-WRED实验案列

Qos-WRED实验案列

Qos-WRED实验案列朱沙一丶项目概述RED对不同类型的数据不能区别对待,重要数据没有得到更好的服务。

WRED(Weighted Random Early Detection,加权随机早期检测)区别对待不同类型的数据,每一类数据采用独立的门限值和丢弃概率。

WRED可以通过IP Precedence和DSCP区分数据。

路由器为华三的设备二丶实验要求项目拓扑如图所示,有两台电脑,pc1和pc2,使用ip-precedence来标识不同数据流, 确保数据重要数据的稳定性。

1.1实验配置:先用CIR把端口限制速度为3M,使网络处于拥塞状态,才能看到实验现象。

interface G0/0/1qos lr outbound cir 3000 cbs 187500 ebs 0分别设置2条ACL,抓取两台主机的IP数据流。

acl number 3000rule 0 permit ip destination 192.168.1.1 0 如果为上传的数据,这里应该为source ip ERED应用接口方向也会发生改变。

acl number 3010rule 0 permit ip destination 172.16.1.1 0 看视频为下载,方向为g0/0/1上的出方向。

出方向接口启用WFQ并且修改队列长度为100(必须先在端口启用WFQ,才能开启WRED)[RT1]int g0/0/1[RT1-GigabitEthernet0/0/1]qos wfq precedence queue-length 100出方向启用WRED:(加权随机早期检测是丢弃策略,必须应用在出接口,数据包先进入路由器,才能执行丢弃策略)[RT1]int g0/0/1[RT1-GigabitEthernet0/0/1]qos wred enable设置WRED的IP优先级,门限值和丢弃概率:[RT1]int g0/0/1[RT1-GigabitEthernet0/0/1]qos wred ip-precedence 7 low-limit 30 high-limit 50 discard-probability 10 (语音数据-当队列长度在30和50之间的时候执行1/10的丢弃概率,队列长度超过50的时候,该数据流全丢弃)[RT1-GigabitEthernet0/0/1]qos wred ip-precedence 3 low-limit 50 high-limit 80 discard-probability 8在QOS类中匹配并标记数据流:[RT1]traffic classifier 3000 名为3000的qos类[RT1-classifier-3000]if-match acl 3000[RT1]traffic behavior 3000[RT1-behavior-3000]remark ip-precedence 7 在qos行为中标记acl3000的ip优先级[RT1]traffic classifier 3010[RT1-classifier-3010]if-match acl 3010[RT1]traffic behavior 3010[RT1-behavior-3010]remark ip-precedence 3进入QOS匹配相应的类和策略:[RT1]qos policy 3000[RT1-qospolicy-3000]classifier 3000 behavior 3000[RT1-qospolicy-3000]classifier 3010 behavior 3010在数据出方向应用策略:[RT1]int g0/0/1[RT1-GigabitEthernet0/0/1]qos apply policy 3000 outbound1.2 实验总结⏹当拥塞严重时队列被塞满,产生尾丢弃⏹尾丢弃可能导致TCP全局同步等严重的问题⏹RED根据一定概率,在拥塞发生之前对数据包进行随机的丢弃⏹根据IP Precendence和DSCP的不同,WRED可以在拥塞发生之前对不同类型的数据包用不同的概率进行随机的丢弃⏹WRED需与WFQ同时使用显示接口的WRED配置情况和统计信息:[Router] display qos wred interface g0/0/1Weighting-constant:加权常数●该指数为权重因子,表征了平均队列长度对实际队列长度变化的敏感程度。

设置网络设备的QoS策略优化网络性能

设置网络设备的QoS策略优化网络性能

设置网络设备的QoS策略优化网络性能随着互联网的快速发展和用户需求的增长,网络性能优化变得尤为重要。

在一个网络中,流量的高峰期和低谷期的差异以及不同应用程序的优先级需求,给网络设备带来了巨大的挑战。

为了解决这些问题,设置网络设备的QoS(Quality of Service,服务质量)策略成为了提高网络性能和用户体验的重要手段之一。

本文将介绍QoS的基本概念、QoS策略的设置步骤以及使用QoS策略优化网络性能的实际案例。

一、QoS的基本概念QoS是一种网络管理的技术,它通过优先级和带宽管理等手段,为不同类型的流量提供不同的服务质量。

QoS可以根据不同应用程序或服务的需求,确保高优先级流量的传输质量,提升网络性能和用户体验。

在设置QoS策略之前,我们需要了解以下几个基本概念:1.1 Differentiated Services (DiffServ)差别化服务是一种实现QoS的方式,它根据流量的优先级和需求,对流量进行分类和处理。

DiffServ为流量分配了不同的服务等级,通过对不同的流量分组进行优先处理,提供更好的传输性能。

1.2 Traffic Shaping流量整形是一种QoS策略,它通过控制流量的发送速率和传输突发性,平滑网络流量和减少网络拥塞。

通过流量整形,我们可以限制特定类型的流量的带宽,并确保其他流量不会被阻塞或丢弃。

1.3 Traffic Policing流量监管是另一种QoS策略,它用于控制流量的发送速率和带宽使用。

与流量整形不同的是,流量监管在流量超过限定速率时丢弃超过部分的数据包,从而确保网络的稳定性。

二、设置QoS策略的步骤为了优化网络性能,我们需要设置合适的QoS策略。

下面是设置QoS策略的基本步骤:2.1 分析网络流量首先,我们需要分析网络流量,了解不同应用程序和服务的传输要求和优先级。

通过网络监测工具,我们可以获取有关流量模式、流量类型和带宽使用的数据。

这样我们就可以更准确地设置QoS策略。

诺基亚7950可扩展路由系统说明书

诺基亚7950可扩展路由系统说明书

Nokia 7950 Extensible Routing SystemRelease 15The Nokia 7950 XRS is a next-generation core routing platform that delivers the scale, efficiency and versatility needed to stay ahead of evolving service demands driven by the cloud, L TE/5G and the Internet of Things.Scale, efficiency and versatility are critical successfactors for network operators in order to sustainprofitable growth in a fiercely competitive marketwhere the only constant is change.Proven innovations lie at the heart of the 7950 XRSfamily, from its silicon to its software and its integrationcapabilities. It allows building a core network withheadroom to meet capacity demands well into thenext decade while covering the full range of capabilitiesto cost-effectively address your IP routing, Internetpeering, multiprotocol label switching (MPLS) andinfrastructure service requirements on a commoncore platform.The conventional wisdom is that cost-efficient scalingof core networks can only be achieved by reducing thescope of functionality and range of flexibility. However,just adding more capacity inevitably results in unwieldy,multi-tier core networks with rapidly diminishingreturns and poor investment protection. The 7950 XRSachieves scale and efficiency without compromisingversatility. This enables network operators to rethinkthese conventions and build a capable and convergedcore network that can scale in a smart way, with superiorreturns on investments.The 7950 XRS is deployed globally by telecom, cable,mobile, utility and private network operators of anysize as well as major Web-scale operators and internetexchange providers.7950 XRS family overview The 7950 XRS family consists of three systems that are designed to meet the needs of global, national, regional and private network operatorsof all sizes: the 7950 XRS-20, -20e and -40.It offers a common platform that addresses the full spectrum of networking needs for public and private internet backbones and peering points, metropolitan and regional aggregation hubsas well as cloud, data center and mobile core infrastructure. This will enable network operators to deliver the immersive ultra-broadband service experiences that consumers aspire to todayand will expect tomorrow.One platform for all servicesThe 7950 XRS addresses the full range of core routing requirements using common hardware that is powered by programmable FP3 routing silicon and runs the proven, resilient and feature-rich Service Router Operating System (SR OS).A flexible, pay-as-you-go software licensing model allows you to build a versatile, reliable and converged core network that evolves with your needs while protecting your hardware investments. Scale with superior economicsA modular and extensible hardware design ensures granular and economical scaling of switching capacity and port density. A 7950 XRS chassis equipped with FP3 hardware delivers up to 16 Tb/s (up to 80 100GE or 800 10GE ports) in a single 19-in rack, and consumes only a single Watt per gigabit of traffic switched. System capacity can be expanded to 32 Tb/s in a back-to-back chassis configuration and each chassis is designed to scale much higher with next generation FP hardware. IP/optical integrationTunable 10G and integrated 100G coherentPM-QPSK tunable DWDM optics enable the7950 XRS to directly interface with the photonic transport layer without requiring optical transponders.A standards-based GMPLS user-network interface (UNI) enables IP/optical control plane integration, allowing the 7950 XRS to efficiently coordinateIP routing and transport requirements across administrative boundaries and to dynamically set up optical segments and end-to-end transport connections.Cross-domain managementThe 7950 XRS is managed by the Nokia Network Services Platform (NSP), supporting integrated element and network management with end-to-end orchestration of network resource provisioning and assurance operations. Operational tools, including the Nokia 5650 Control Plane Assurance Manager (CPAM), provide additional visibility and flexibilityin monitoring and trouble-shooting IP control plane issues.Carrier SDN integrationThe 7950 XRS and SR OS enable multivendor SDN control integration through OpenFlow, PCEP and NETCONF/YANG. Network operators can leverage the 7950 XRS in combination with the NSP to introduce scalable and integrated carrier SDN control across IP, MPLS, Ethernet and optical transport layers.The NSP supports unified service automation and network optimization with comprehensive path computation capabilities to enable source-based routing and traffic steering with segment routing support, online traffic engineering and resource optimization, and elastic bandwidth services for dynamic cloud applications.7950 XRS-40The Nokia 7950 XRS-40 provides32 Tb/s of routing capacity in a single system when fully equipped with FP3 hardware. The system comprises 40 slots in a dual-chassis configuration of two 7950 XRS-20or two 7950 XRS-20e systems, with each slot supporting 400 Gb/s of full duplex aggregate interface capacity. The two systems are interconnected through optical backplane cabling and can be placed up to 30 meters apart. One chassis will act as the master and assume system control overthe extension chassis as well. Designed to meet the needs of today’s largest Internet backbones and aggregation points, a single 7950 XRS-40 core router can handle up to 160 100GE or 1600 10GE interfaces without oversubscription and achieve full port density without requiring cabling breakout panels.7950 XRS-20The Nokia 7950 XRS-20 provides16 Tb/s of routing capacity in a single19-in rack when fully equipped withFP3-based hardware, and its chassisand common hardware is designedto scale much higher in the future.With 20 slots, each initially capableof 400 Gb/s of full duplex aggregateinterface capacity, the systemsupports up to 80 100GE or 80010GE ports in a single rack usingstandards-based pluggable opticsand without requiring additionalbreakout panels for cabling.The 7950 XRS-20 system is availablein an extensible and a stand-aloneconfiguration. The extensibleconfiguration is equipped with opticalbackplane connectors and can beupgraded in-service to a 7950 XRS-40back-to-back configuration to doublesystem capacity. The standaloneconfiguration can be made extensibleby exchanging the Switch FabricModules.7950 XRS-20eThe Nokia 7950 XRS-20e runsSR OS release 13.0 or higher andis functionally compatible withthe XRS-20. All XRS-20 hardwarecomponents except the fan traysand XRS Control Modules areinterchangeable.The “Universal” chassis variantsupports all AC and DC poweroptions and is equipped with aPower Connection Panel at the rear.The “AC/HVDC” variant is cabled atthe front and has a blank rear panel.The 7950 XRS-20e introduces anew XRS Control Module (XCM)with additional air-intake capacity.Air movement and noise levelsare further improved through anupgraded cooling fan assemblywith slanted centrifugal impellertrays and 2+1 redundancy.Common elements and attributesThe 7950 XRS core router family shares fundamental attributes that ensure consistency, operational ease of use, and investment protection for network operators.Routing siliconThe 7950 XRS leverages internally developedNPU routing silicon to ensure optimal performance and scaling of a rich and complete Layer 2 and Layer 3 feature set that addresses all core deployment scenarios. The 400G FP3 chipset is the third-generation NPU and provides the perfect geometry for high-density 10, 40, 100 and 400G interface modules. It offers deterministic forwarding performance with advanced traffic management features and energy-efficient power gating techniques.These silicon innovations drive the high levelof flexibility and performance needed for converged backbone and metro core deployments, including IP routing and peering, MPLS switching, VPN infrastructure services and data center interconnection applications.Interface modulesThe Nokia 7950 XRS uses a pair of complementary modules to support current and future interfaces. XMA Control Modules (XCMs) contain a slot-level control plane subsystem and switch fabric interface. XRS Media Adapters (XMAs) contain the forwarding complex and provide a wide range of GE, 10GE,40GE and 100GE interface options.A flexible software licensing scheme allowsfor customizing XMAs for diverse core router applications, with configurable quality of service (QoS) granularity. This enables operators to consolidate core routing systems on a single platform, and to rapidly respond to evolving requirements with minimal impact and maximum investment protection.Operating systemThe 7950 XRS family is based on the proven SR OS, carrying forward over a decade of experience in the IP networks of more than 750 network operators worldwide. With a single common OS across the Nokia routing portfolio, network operators benefit froman extensive track record of reliability in the field and a full suite of features to enable resiliency, high availability and in-service software upgrade (ISSUs). Optical integrationMany operators are looking to optimize the overall efficiency of the core through closer integrationof the IP and optical domains. Tunable, pluggable DWDM optics for 10GE and 100GE interfaces are available for all platforms. Multi-vendor IP/optical control plane integration is supported by meansof the GMPLS UNI.Power and cooling efficiencyThe 7950 XRS system design incorporates intelligent power management capabilitiesto monitor power consumption of individual components, assure power safety thresholds,and manage power-up and power-down priorities in the event of degraded power availability. Other key enhancements include clock gating techniques that dynamically reduce power to system components not in use.Redundant, modular fan trays that are linearly modulated provide appropriate and efficient cooling with reduced noise levels. The 7950 XRS-20 uses two linear, 1+1 redundant fan trays in a stacked configuration for primary system cooling whilethe XRS-20e uses three impeller fan trays in aside-by-side configuration.A “pull” airflow design, in combination with impedance panels and air guides, ensures an even distribution of air to every section of the system. Hot air exhaust through the back of the chassis ensures a clean separation between the hot and cold aisles. An optional top plenum accessory is available for the 7950 XRS-20 to enable hot air exhaust at the top of the chassis for additional cooling efficiency.Hardware overviewAll common equipment components are redundant and field replaceable to maximize system uptime. Chassis Control Modules (CCMs)Redundant CCMs support operator access tothe Nokia 7950 XRS control and management interfaces. The CCMs are located at the top, and each CCM has an LCD touch-screen display and supports interfaces for timing, management, alarms and memory expansions.Advanced Power Equalization Modules (APEQs) APEQs provide power for the 7950 XRS and include built-in intelligence to monitor and communicate available power budget versus actually consumed power. The low voltage DC APEQs deliver up to 2800W each. The high voltage DC APEQs take260-400 V and provide 3000W each. AC APEQs take 200-240 V single phase and deliver 3000W each. APEQs support cost-effective modular expansion as required.Fan traysFan trays provide system cooling for the 7950 XRS. Redundant fans can be controlled independently and fan speed is linearly modulated to allow for the optimal balancing of cooling, power and noise. The 7950 XRS-20 supports two stacked horizontal fan trays with 1+1 redundancy. The XRS-20e chassis variants support three side-by-side impeller fan trays with 2+1 redundancy.Switch Fabric Modules (SFMs)SFMs enable the line-rate connectivity betweenall slots of a 7950 XRS chassis. The fabric cardsare N+1 redundant with active redundancy and graceful capacity degradation in case multiple SFMs fail. There are two types of SFMs. The first is dedicated to standalone system operation of the 7950 XRS-20 and XRS-20e. The second is equipped with optical connectors to support back-to-back configuration in a 7950 XRS-40 system.Control Processor Modules (CPMs)CPMs provide the management, security and control plane processing for the Nokia 7950 XRS. Redundant CPMs operate in a hitless, stateful, failover mode. Central processing and memoryare intentionally separated from the forwarding function on the interface modules to ensure utmost system resiliency. Each CPM contains a full FP3 complex to protect against Denial of Service attacks. XRS Media Adapters (XMAs)XMAs provide the interface options for the7950 XRS, including high-density GE, 10GE, 40GE and 100GE interfaces. They contain an FP3-based forwarding complex that performs typical functions such as packet lookups, traffic classification, processing and forwarding, service enablement and QoS. Each XMA also provides specific interface ports, physical media and optical functions. The range of interface modules and slot capacitywill expand over time, along with overall system capacity, in order to accommodate the evolving needs of network operators while protectingtheir 7950 XRS hardware investments.XRS Control Modules (XCMs)XMAs are equipped in an appropriate XCM. The XCMs contain a slot-level control plane subsystem and fabric interface to interconnect to the switch fabric modules (SFMs) via the chassis mid-plane. XMCs connect via a mid-plane to deliver 800 Gb/s full duplex slot capacity to a pair of 400G XMAs or 200G C-XMAs. The XCM variants for the 7950 XRS-20 and XRS-20e each deliver 800 Gb/s full duplex slot capacity and support the full range of FP3 XMAs and C-XMAs. The flexibility and modularity of XCMs and XMAs allow network operators to granularly configure each Nokia 7950 XRS with its desired range of Ethernet interfaces to meet the demands of growing core networks.Technical specificationsTable 1. Technical specifications for the Nokia 7950 XRS familySystem expansion—32 Tb/s (back-to-back)32 Tb/s (back-to-back) System design Mid-plane Mid-plane Mid-planeInterface slots402020Number of XMAs (400G line card)40 per system20 per system20 per system Number of C-XMAs (200G linecard)40 per system20 per system20 per systemCommon equipment redundancy CPM (1+1), CCM (1+1), DC APEQ(N+1), AC APEC (N+N), SFM (14+2),fan trays (1+1), power termination(1+1)CPM (1+1), CCM (1+1), DC APEQ(N+1), AC APEC (N+N), SFM (7+1),fan trays (1+1), power termination(1+1)CPM (1+1), CCM (1+1), DC APEQ(N+1), AC APEC (N+N), SFM (7+1),fan trays (2+1), power termination(1+1)Hot-swappable modules CPM, CCM, XCM, XMA, C-XMA,APEQ, SFM, fans CPM, CCM, XCM, XMA, C-XMA,APEQ, SFM, fansCPM, CCM, XCM, XMA, C-XMA,APEQ, SFM, fansDimensions 2 x standard 19-in racks39 RU• Height: 173 cm (68.25 in)• Width: 44.5 cm (17.5 in)• Depth: 91 cm (36 in)1 standard 19-in rack39 RU (44 RU with top plenum)• Height: 173 cm (68.25 in)• Width: 44.5 cm (17.5 in)• Depth: 91 cm (36 in)1 standard 19-in rack44 RU (no top plenum)• Height: 195.6 cm (77 in)• Width: 44.5 cm (17.5 in)• Depth: 106.3 cm (41.9 in)Weight* (max)1,070.5 kg (2360 lb)535.2 kg (1180 lb)612.35 (1350 lb)Power• -48 V DC (2 x 12 60A/80A inputs)• 260-400 V DC (2 x 12 inputs)• 200-240 V AC (2 x 12 inputs)• -48 V DC (12 60A/80A inputs)• 260-400 V DC (12 inputs)• 200-240 V AC (12 inputs)• -48 V DC (12 60A/80A inputs)• 260-400 V DC (12 inputs)• 200-240 V AC (12 inputs)Cooling Front/bottom to top/back Front/bottom to top/back Front/bottom to back * Weights and dimensions are approximate and subject to change. Refer to the appropriate installation guide for the current weights and dimensions.Table 2. Nokia 7950 XRS XMA/C-XMA support per chassis type10GBASE (200G C-XMA)20SFP+800400400 10GBASE (400G XMA)40SFP+1600800800 40GBASE (200G C-XMA)6QSFP+240120120 100GBASE (200G C-XMA)2CFP804040 100GBASE (400G XMA)4CXP, CFP21608080 100G DWDM (200G XMA)2LC (OTU4)804040 400G DWDM (400G XMA)1LC (dual carrier)402020Feature and protocol support highlights Protocol support within the 7950 XRS family includes (but is not limited to):• Intermediate System-to-Intermediate System (IS-IS), Open Shortest Path First (OSPF), and Multiprotocol Border Gateway Protocol (MBGP) IPv4 and IPv6 unicast routing• Internet Group Management Protocol (IGMP), Multicast Listener Discovery (MLD), Protocol Independent Multicast (PIM), and Multicast Source Discovery Protocol (MSDP) IPv4 andIPv6 multicast routing• MPLS Label Edge Router (LER) and Label Switching Router (LSR) functions, with support for seamless MPLS designs• Label Distribution Protocol (LDP) and Resource Reservation Protocol (RSVP) for MPLS Signaling and Traffic Engineering with Segment Routing support, Point-to-Point (P2P) and Point-to-Multipoint (P2MP) Label Switched Paths (LSPs) with Multicast LDP (MLDP) and P2MP RSVP, weighted Equal-Cost Multi-path (ECMP),Inter-AS Multicast VPN (MVPN) and Next Generation Multicast VPN (NG-MVPN)• P2P Ethernet virtual leased lines (VLLs), Ethernet VPNs (EVPNs), EVPN-MLDP, EVPN-VPWS, Virtual Extensible LAN (VXLAN), EVPN-VXLAN to VPLS/ EVPN-VPLS gateway functions• Multipoint Ethernet VPLS and IP VPNs for usein delivering core infrastructure services• Ethernet port expansion through remote Nokia 7210 Service Access Switch (SAS) Ethernet satellites, each offering 24/48GE ports over a4 x 10GE Link Aggregation Group (LAG) under 7950 XRS control• Unicast Reverse Path Forwarding (uRPF), RADIUS/TACACS+, and comprehensive control plane protection features for security • Extensive OAM features, including Cflowd, Ethernet Connectivity Fault Management (CFM) (IEEE 802.1ag, ITU-T Y.1731), Ethernet in the First Mile (EFM) (IEEE 802.3ah), Two-Way Active Measurement Protocol (TWAMP), Bi-Directional Fault Detection (BFD), and a full suite of MPLS OAM tools including GMPLS UNI• Intelligent packet classification, queue servicing, policing and buffer management• Industry-leading high availability, including nonstop routing, nonstop services, ISSU,fast reroute, pseudowire redundancy, ITU-T G.8031 and G.8032, weighted mixed-speed link aggregation• Management via CLI, SNMP MIBs, NETCONF/ YANG and service assurance agent (SAA) with comprehensive support through the Nokia 5620 SAM• Multivendor SDN control integration through OpenFlow, PCEP, BGP-LS interface support Environmental specifications• Operating temperature: 5°C to 40°C(41°F to 104°F)• Operating relative humidity: 5% to 85%• Operating altitude: Up to 4000 m (13,123 ft)at 30°C (86°F)Safety standards and compliance agency certifications • IEC/EN/UL/CSA60950-1 Ed2 Am2• FDA CDRH 21-CFR 1040• IEC/EN 60825-1• IEC/EN 60825-2Nokia is a registered trademark of Nokia Corporation. Other product and company names mentioned herein may be trademarks or trade names of their respective owners. Nokia Oyj Karaportti 3 FI-02610 Espoo FinlandTel. +358 (0) 10 44 88 000Product code: SR1702007527EN (March)EMC emission• ICES-003 Class A• FCC Part 15 Class A(with EMI/Protection panel)• EN 55032 Class A • CISPR 32 Class A • AS/NZS CISPR 32 Class A • VCCI Class A • KN 32 Class A • EN 61000-3-2• EN 61000-3-3EMC immunity• ETSI EN 300 386• EN 55024• KN 35Environmental• ETSI EN 300 019-2-1 Storage Tests, Class 1.2• ETSI EN 300 019-2-2 Transportation Tests, Class 2.3• ETSI EN 300 019-2-3 Operational Tests, Class 3.2• ETSI EN 300 019-2-4, pr A 1 Seismic• ETSI EN 300 132-2 DC Power Supply Interface • ETSI EN 300 132-3-1 HVDC Power Supply Interface • WEEE • RoHS • China CRoHSNetwork Equipment Building System (NEBS)• NEBS Level 3• RBOC requirements –ATIS-0600020 –ATIS-0600010.3 –ATIS-0600015 –ATIS-0600015.03 –ATT-TP-76200 –VZ.TPR.9205 TEEER –VZ.TPR.9305MEF certifications• CE 2.0–Certified (on E-LAN, E-Line, E-Tree and E-Access MEF service types) –100G Certified (on E-Line and E-Access MEF service types)• CE 1.0 (MEF 9 and MEF 14) –Certified。

QOS技术原理及配置优质PPT课件

QOS技术原理及配置优质PPT课件

RSVP原理
我要预留
2Mbps带宽
OK!
我要预留
2Mbps带宽
OK!
OK!
开始通信
OK!
报文分类及标记
ACL , IP优先级
• 报文分类及标记是QoS 执行服务的基础
• 报文分类使用技术:ACL和IP优先级
• 根据分类结果交给其它模块处理或打标记(着色)
供核心网络分类使用
流分类
流即业务流(traffic),指所有通过交换机的报文。
的报 文将之标记为其它的802.1p 优先级后再进行转发;
改变DSCP 优先级并转发:比如对评估结果为“符合”或

“不符合”的报文,将之标记为其它的DSCP优先级后再进
行转发
流量整形
TS 示意图
端口限速
端口限速(Line Rate)是指基于端口的速率限制,它对
端口接收或发送报文的总速率进行限制
端口限速也是采用令牌桶进行流量控制。如果在设备的
A
网络传输延时
端到端的延时
处理延时
时间t
抖动
Int3
发送
1
2
D2
D3=D2=D1
1
D1
接收
带宽限制
10M
IP
我要2M
QoS技术优点
• 可以限制骨干网上FTP(文件传输)使用的带
宽,也可以给数据库访问以较高优先级
• 对于ISP(互联网服务提供商),其用户可能
传送语音、视频或其他实时业务,QoS使ISP
流分类(traffic classification)是指采用一定的规
则识别符合某类特征的报文,它是有区别地进行
服务的前提和基础。
分类规则:

5GNRQOS概述

5GNRQOS概述

5GNRQOS概述
5G NR QoS(5G网络接入)是5G技术中新增的一种服务质量控制(QoS Control)机制,用于确保5G用户终端(UE)能够以可接受的质量享
受服务。

5G NR QoS的设计是基于3GPP标准的3GPP Release 15和Release 16,它提供了更加先进、可靠和灵活的服务质量控制机制,能够
支持对低时延、高精度和高吞吐量的服务。

5GNRQoS通过定义一套技术规范,可以满足不同消费者的需求,从而
最大限度地增强用户体验(UX)。

广泛应用于最新的5G网络,为各种应
用(例如高清视频流)提供可靠的服务质量,同时可以改善传统4G网络
的实时通信(例如视频会议)。

5GNRQoS也可以显著增加网络容量和效率,从而提高系统的性能和效率。

5G NR QoS的设计目标是动态地管理UE的服务质量,从而让UE能收
到最佳的服务质量。

本文主要介绍了具体的QoS机制,即QoS保障层(GBR)、QoS保护层(Non-GBR)、QoS分类和QoS标识等概念。

5G NR QoS可以在网络前端实现动态资源分配和动态服务质量控制,以保证使用
给定资源的服务质量一致。

首先,5GNRQoS提供了一套有效的QoS管理框架,可以识别不同类型
的应用,从而使系统能够有效地识别不同类型的服务,并对其进行QoS控制。

qos队列调度算法研究及应用

qos队列调度算法研究及应用

qos队列调度算法研究及应用QoS (Quality of Service)队列调度算法是一种在交换节点上应用的机制,这种机制可以实现队列的优先级调度,增强网络的QoS保证能力。

既可以给实时流带来低延迟的吞吐量,也可以给非实时流带来适量的带宽。

队列调度算法的目的是通过合理的调度策略,使网络资源的分配更加公平,能够保证给各种类型的流实现可预测的质量。

研究QoS调度算法的主要目的是提高网络服务质量,而研究具体算法旨在解决网络质量问题。

常用的QoS队列调度算法有Weight Fair Queuing(WFQ)、Virtual Clock(VC)等。

WFQ算法基本思想是,在网络节点上通过对队列中流量带宽数量进行计算,实现对流量的优先级调度,从而提高网络资源的利用率。

该算法中使用了流调度的虚拟时钟技术,这种技术可以实现多用户同时使用网络中的资源,把真实时间和虚拟时间关联起来,确定每个用户在虚拟时钟中的上下文,通过调整系统参数,调整每个用户在虚拟时钟中的位置,以实现质量保障。

Virtual Clock算法是一种把传输物理层、网络层和传输层联系在一起的机制,它可以把传输速率转换到流量管理领域,为QoS保证提供一种解决方案。

算法的具体实现是使用一个有状态的令牌桶作为时钟,根据每个流的传输速率,将令牌桶对每个流的传输进行控制,实现每个流传输的QoS规定。

应用QoS队列调度算法可以保证网络资源的公平分配,提高网络服务质量。

目前,QoS队列调度算法应用较为广泛,主要应用在无线传输技术、服务流技术、数据传输和路由等领域。

QoS队列调度算法对实现有效的流量控制具有重要作用。

同时,这种算法在智能网络中也有重要的作用,可以实现路由优化、多媒体流的确认以及实时任务的优先调度。

qos-policy实验

qos-policy实验

Qos-policy实验朱沙一丶项目概述使用Qos-policy做限速,来实现对上传速率的控制。

路由器为华三的设备二丶实验要求使用Qos-policy在进方向做限速在出方向做流量整形,PC1,PC2上传速率控制为1M。

1.1实验配置:一丶使用QOS policy car限制进方向链路上传速度。

traffic classifier 123 创建一个名为123的类if-m atch dscp default 使用dscp默认值traffic behavior 123 配置qos行为car cir 1000 使用car限制速度为1Mqos policy 123classifier 123 behavior 123 进入qos策略,匹配类和相应的行为int e0/1 进方向应用qos policyqos apply policy 123 inboundint e0/2qos apply policy 123 inbound实验现象:实验截图为FTP服务器,每个人差不多有120K的上传速度。

总上传速度240K左右。

二丶使用QOS policy gts在出方向使用GTS流量整形来限制速度。

traffic classifier 321 创建一个名为123的类if-match any 匹配任何traffic behavior 321 配置qos行为gts cir 1000 使用gts限制上传速度为1Mqos policy 321classifier 321 behavior 321 进入qos策略,匹配类和相应的行为int e0/0qos apply policy 321 outbound 出方向应用qos policy实验现象:实验截图为FTP服务器。

由于在出方向使用GTS对流量整形为1M,总上传速度为125K左右,PC1和PC2都只有60K的速度。

三丶把进方向和出方向都修改为8M。

traffic behavior 123car cir 8000traffic behavior 321gts cir 8000实验现象:实验截图为FTP服务器。

INTERNATIONAL JOURNAL OF WIRELESS AND MOBILE COMPUTING (IJWMC) 1 A Biologically Inspired Qo

INTERNATIONAL JOURNAL OF WIRELESS AND MOBILE COMPUTING (IJWMC) 1 A Biologically Inspired Qo

A Biologically Inspired QoS Routing Algorithm forMobile Ad Hoc NetworksZhenyu Liu,Marta Z.Kwiatkowska,and Costas ConstantinouAbstract—This paper presents an Emergent Ad hoc Routing Algorithm with QoS provision(EARA-QoS).This ad hoc QoS routing algorithm is based on a swarm intelligence inspired routing infrastructure.In this algorithm,the principle of swarm intelligence is used to evolutionally maintain routing information. The biological concept of stigmergy is applied to reduce the amount of control traffic.This algorithm adopts the cross-layer optimisation concept to use parameters from different layers to determine routing.A lightweight QoS scheme is proposed to provide service-classified traffic control based on the data packet characteristics.The simulation results show that this novel routing algorithm performs well in a variety of network conditions.Index Terms—MANET,routing,QoS,swarm intelligence.I.I NTRODUCTIONM OBILE ad hoc networks(MANETs)are wireless mo-bile networks formed munication in such a decentralised network typically involves temporary multi-hop relays,with the nodes using each other as the relay routers without anyfixed infrastructure.This kind of network is veryflexible and suitable for applications such as temporary information sharing in conferences,military actions and disaster rescues.However,multi-hop routing,random movement of mobile nodes and other features unique to MANETs lead to enormous overheads for route discovery and maintenance.Furthermore, compared with the traditional networks,MANETs suffer from the resource constraints in energy,computational capacities and bandwidth.To address the routing challenge in MANETs,many ap-proaches have been proposed in the literature.Based on the routing mechanism for the traditional networks,the proactive approaches attempt to maintain routing information for each node in the network at all times[1]–[3],whereas the reactive approaches onlyfind new routes when required[4]–[6].Other approaches make use of geographical location information for routing[7],[8].Those previous works only provide a basic “best effort”routing functionality that is sufficient for con-ventional applications such asfile transfer or email download. To support real-time applications such as V oIP and video stream in MANETs,which have a higher requirement for delay,jitter and packet losses,provision of Quality-of-Service (QoS)is necessary in addition to basic routing functionality. Z.Liu and M.Z.Kwiatkowska is with School of Computer Science,The University of Birmingham,Birmingham,England B152TT.C.Constantinou is with the Department of Electronic Electrical and Computer Engineering,The University of Birmingham,Birmingham,England B152TT.Given the nature of MANETs,it is difficult to support real-time applications with appropriate QoS.In some cases it may be even impossible to guarantee strict QoS requirements.But at the same time,QoS is of great importance in MANETs since it can improve performance and allow critical information to flow even under difficult conditions.At present,the most fundamental challenges of QoS support in MANETs concern how to obtain the available bandwidth and maintain accurate values of link state information during the dynamic evolution of such a network[9].Based on common techniques for QoS provision in the Internet,some researchers proposed the integration of QoS provision into the routing protocols[10],[11].However,since these works implicitly assumed the same link concept as the one in wired networks,they still do not fully address the QoS problem for MANETs.In this paper,we propose a new version of the self-organised Emergent Ad hoc Routing Algorithm with QoS provisioning(EARA-QoS).This QoS routing algorithm uses information from not only the network layer but also the MAC layer to compute routes and selects different paths to a destination depending on the packet characteristics.The underlying routing infrastructure,EARA originally proposed in[12],is a probabilistic multi-path algorithm inspired by the foraging behaviour of biological ants.The biological concept of stigmergy in an ant colony is used for the interaction of local nodes to reduce the amount of control traffic.Local wireless medium information from the MAC layer is used as the artificial pheromone(a chemical used in ant communications) to reinforce optimal/sub-optimal paths without the knowledge of the global topology.One of the optimisations of EARA-QoS over EARA is the use of metrics from different layers to make routing decisions. This algorithm design concept is termed as the cross-layer design approach.Research[13]has shown the importance of cross-layer optimisations in MANETs,as the optimisation at a particular single layer might produce non-intuitive side-effects that will degrade the overall system performance.Moreover, the multiple-criteria routing decisions allow for the better usage of network characteristics in selecting best routes among multiple available routes to avoid forwarding additional data traffic through the congested areas,since the wireless medium over those hotspots is already very busy.The parameters for measuring wireless medium around a node depend largely on the MAC layer.In this paper,we focus on the IEEE802.11 DCF mode[14],since it is the most widely used in both cellular wireless networks and in MANETs.This cross-layer technique of using MAC layer information can be appliedeasily to other MAC protocols.In addition to the basic routing functionality,EARA-QoS supports an integrated lightweight QoS provision scheme.In this scheme,traffic flows are classified into different service classes.The classification is based on their relative delay bounds.Therefore,the delay sensitive traffic is given a higher priority than other insensitive traffic flows.The core technique of the QoS provision scheme is a token bucket queuing scheme,which is used to provide the high priority to the real-time traffic,and also to protect the lower-priority traffic from star-vation.Experimental results from simulation of mobile ad hoc networks show that this QoS routing algorithm performs well over a variety of environmental conditions,such as network size,nodal mobility and traffic loads.II.B ACKGROUNDIn this section,we give a brief introduction to background knowledge on ant colony heuristics,and the QoS provision techniques in MANETs.A.Foraging Strategies in AntsOne famous example of biological swarm social behaviour is the ant colony foraging [15](see Figure 1).Many ant species have a trail-laying,trail-following behaviour when foraging:individual ants deposit a chemical substance called pheromone as they move from a food source to their nest,and foragers follow such pheromone trails.Subsequently,more ants are attracted by these pheromone trails and in turn reinforce them even more.As a result of this auto-catalytic effect,the optimal solution emerges rapidly.In this food searching process a phenomenon called stigmergy plays a key role in developing and manipulating local information.It describes the indirect communication of individuals through modifying theenvironment.Fig.1.All Ants Attempt to Take the Shortest PathFrom the self-organisation theory point of view,the be-haviour of the social ant can be modelled based on four elements:positive feedback,negative feedback,randomness and multiple interactions [16].This model of social ants using self-organisation theories provides powerful tools to transfer knowledge about the social insects to the design of intelligent decentralised problem-solving systems.B.Quality-of-Service in MANETsQuality-of-Service (QoS)provision techniques are used to provide some guarantee on network performance,such as average delay,jitter,etc.In wired networks,QoS provision can generally be achieved with the over-provisioning of re-sources and with network traffic engineering [17].With the over-provisioning approach,resources are upgraded (e.g.fibre optic data link,advanced routers and network cards)to make networks more resistant to resource demanding applications.The advantage of this approach is that it is easy to be implemented.The main disadvantage of this approach is that all the applications still have the same priority,and the network may become unpredictable during times of bursting and peak traffic.In contrast,the idea of the traffic engineering approach is to classify applications into service classes and handle each class with a different priority.This approach overcomes the defect of the former since everyone is following a certain rule within the network.The traffic engineering approach has two complemen-tary means to achieve QoS provisioning,Integrated Services (IntServ)and Differentiated Services (DiffServ).IntServ [18]provides guaranteed bandwidth for flows,while DiffServ [19]provides hard guarantees for service classes.Both of the approaches rely on the possibility to make bandwidth reservations.The former was used in ATM (Asynchronous Transfer Mode)[20]and is today the method of achieving QoS in RSVP-IntServ [21].On the other hand,in the DiffServ approach,no reservation is done within the network.Instead,QoS is achieved by mechanisms such as Admission Control ,Policy Manager ,Traffic Classes and Queuing Schedulers .These mechanisms are used to mark a packet to receive a particular forwarding or dropping treatment at each node.Based on QoS provision techniques in wired networks,many QoS approaches are proposed to provide QoS services for MANETs.Flexible QoS Model for MANETs (FQMM)[22],is the first QoS approach for MANETs,which combines knowledge on IntServ/DiffServ in wired networks with con-sideration of MANETs.As an essential component to achieve the QoS provisioning,QoS routing algorithms tightly integrate QoS provisioning into routing protocols.The QoS version of AODV (QoS-AODV)[23],the Core-Extraction Distributed Ad Hoc Routing (CEDAR)protocol [10],the Multimedia Support for Mobile Wireless Networks (MMWN)protocol [11],and the ticket-based protocols [24]are examples of QoS routing algorithms proposed for MANETs.On the other hand,QoS signaling techniques are inde-pendent of the underlying routing protocols.The In-band Signalling for QoS in Ad-Hoc Mobile Networks (INSIGNIA)algorithm [25]is the typical signaling protocol designed exclusively for MANETS.The idea of CEDAR,MMWN,and ticket-based protocols is to disseminate link-state information across the network in order to enable other nodes to find routes that meet certain QoS criteria,like the minimum bandwidth.On the other hand,INSIGNIA piggybacks resource reservations onto data packets,which can be modified by intermediate nodes to inform the communication endpoint nodes in case of lack ofresources.All those approaches are based on the idea that the wireless links between mobile nodes have certain QoS related properties,in particular a known amount of available bandwidth,and that nodes are able to give guarantees for traffic traversing these links.III.C RITIQUE OF E XISTING Q O S A PPROACHES INMANET SNowadays,most of the QoS provisioning techniques are derived from the QoS approaches of the wired networks. However,QoS support approaches proposed in wired networks are based on the assumption that the link characteristics such as bandwidth,delay,loss rate and error rate must be available and manageable.However,given the challenges of MANETs, e.g.dynamic topology and time-varying link capacity,this assumption does not apply any longer.Thus,applying the concepts of wired traffic engineering QoS approaches directly to MANETs is extremely difficult.Generally,the situation in MANETs is completely different from those in wired networks.In wireless networks,the available bandwidth undergoes fast time-scale variations due to channel fading and errors from physical obstacles.These effects are not present in wired networks.In MANETs,the wireless channel is a shared-access medium,and the available bandwidth even varies with the number of hosts contending for the channel.Below we analyse why the IntServ/DiffServ models are not appropriate for MANETs respectively. IntServ based approaches are not applicable for MANETs mainly due to two factors,huge resource consumption and computation power limitation.Firstly,to support IntServ,a huge amount of link state information has to be built and main-tained for each mobile node.The amount of state information increases proportionally with the number offlows,which is also a problem with the current IntServ QoS scheme.Secondly, current wireless networks employ two major MAC techniques, the single-channel approach and the multiple channel ap-proach.With single-channel approach(e.g.IEEE802.11[14]), all nodes share the same channel and therefore potentially interfere with each other.With a multiple-channel approach (e.g.Bluetooth[26]or CDMA[27]),nodes can communicate on several channels simultaneously.Both of the two MAC techniques have a similar bandwidth reservation mechanism. This common mechanism requires a transmission schedule to define time slots,in which nodes take their turns periodically. For each slot,its duration and a set of possible simultaneous transmissions must be defined.However,in wireless networks, the problem offinding an optimal schedule is proved to be NP-complete[28],which is a fundamental limitation of QoS provisioning in wireless networks.On the other hand,the DiffServ approach is a lightweight QoS model for interior routers since individual stateflows are aggregated into sets of service classes whose packets are treated differently at the routing nodes.This makes routing a lot easier in the network.Thus this approach could be a potential solution for MANETs.Even though it is not practical to provide a hard separation of different service classes in MANETs,relative prioritisation is possible in such a way that traffic of a certain class is given a higher or lower priority than traffic of other service classes.One solution would be to divide the traffic into a predefined set of service classes that are defined by their relative delay bounds,such as delay sensitive(realtime)and insensitive(bulk)traffic.Realtime traffic should be given higher priority than bulk traffic.No absolute bandwidth guarantees are provided.Some work based on service differentiation rather than resource reservations in MANETs already exists[29].IV.D ESCRIPTION OF EARA-Q O SEARA-QoS is an on-demand multipath routing algorithm for MANETs,inspired by the ant foraging intelligence.This algorithm incorporates positive feedback,negative feedback and randomness into the routing computation.Positive feed-back originates from destination nodes to reinforce the existing pheromone on good paths.Ant-like packets,analogous to the ant foragers,are used to locallyfind new paths.Artificial pheromone is laid on the communication links between nodes and data packets are biased towards strong pheromone,but the next hop is chosen probabilistically.To prevent old routing solutions from remaining in the current network status,expo-nential pheromone decay is adopted as the negative feedback. Each node using this algorithm maintains a probabilistic routing table.In this routing table,each route entry for the destination is associated with a list of neighbour nodes.A probability value in the list expresses the goodness of node as the next hop to the destination.For each neighbour, the shortest hop distance to the destination and the largest sequence number seen so far are also recorded.In addition to the routing table,each node also possesses a pheromone table.This table tracks the amount of pheromone on each neighbour link.The table may be viewed as a ma-trix with rows corresponding to neighbourhood and columns to destinations.There are three threshold values controlling the bounds on pheromone in the table.They are the upper pheromone that prevents extreme differences in pheromone, the lower pheromone,below which data traffic cannot be forwarded,and the initial pheromone that is assigned when a new route is found.In addition to the routing data structures present above,the following control packets are used in EARA-QoS to perform routing computation:Route Request Packet(RQ)containing destination ad-dress,source address and broadcast ID.Route Reply Packet(RP)containing source address,des-tination address,sequence number,hop account and life-time.Reinforcement Signal(RS)containing destination ad-dress,pheromone value and sequence number.Local Foraging Ant(LFA)containing source address (the node that sent LFA),the least hop distance from the source to the destination,stack of intermediate node address and hop count.Hello Packet(HELLO)containing source(the node that sent Hello)address and hop count(set to0).A.Parameters of Lower Layers1)The Average MAC Layer Utilisation:Thefirst metric is the average MAC layer utilisation for a node.This metric measures the usage of the wireless medium around that node. As the instantaneous MAC layer utilisation at a node is either (busy)or(idle),we average this value over a period of time window as follows:(1) where is the time when the medium is busy in the window.This average MAC utilisation indicates the degree to which the wireless medium around that node is busy or idle.We consider the instantaneous MAC layer utilisation level at a node to be1when the wireless medium around that node either detects physical carrier to be present or is deferring due to virtual carrier sensing,inter-frame spacing,or backoff.In addition,we also consider the medium is busy at any time when the node has at least one packet in the transmission queue.2)The Transmission Queue Heuristic:The second metric isa heuristic value that is calculated with the network interface transmission queue length in the current node.Apart from the media status,the transmission queue length is also a key factor that can affect the packet latency or packet drop due to the size limit on the queue length.We define the heuristic value with the following rules.If the outgoing network interface employs a single queue scheme,the heuristic value is defined as:(2) where is the length(in bytes waiting to be sent)of the interface queue in node,and is the maximum packet bytes allowed in the queue.If the network interface employs the multiple virtual queue scheme for each outgoing link,the heuristic value is defined as:(3)where is the length(in bytes waiting to be sent)of the virtual queue of the link in node and denotes the neighbourhood of node as a next-hop to some destination.3)The Average MAC Layer Delay:The last metric is the MAC layer delay for the link.The MAC layer delay is defined as the interval from when the RTS frame is sent at node to when the data frame is received successfully at node.The average MAC delay is obtained by averaging these values over a time window as follows:(4)where is the time interval in the window,and is a coefficient.This average MAC delay indicates the degree of interference.In regions where there is a lot of interference from other nodes,MAC delay is high due to the contentionof the channel.B.Data PropagationWhen multiple virtual queue scheme is employed,the rout-ing probability value is computed by the composition ofthe pheromone values,the local heuristic values and the linkdelays as follows:(5) where,and()are tunable parametersthat control the relative weight of pheromone trail,MAC delay and heuristic value,and is the neighbourhood as a next-hop to some destination.Incorporating the heuristic value and link delay in the rout-ing computation makes this algorithm possess the congestionawareness property.Based on the probabilistic routing table, data traffic will be distributed according to the probabilitiesfor each neighbour in the routing table.The routing algorithmexhibits load balancing behaviour.Nodes with a large number of packets in the buffer are avoided.The EARA-QoS algorithm consists of several components.They are the route discovery procedure,the positive and neg-ative reinforcement,and the local connectivity management.C.Route DiscoveryWe use a similar route discovery procedure as describedin[12].On initialisation,a neighbourhood for each node is built using the single-hop HELLO messages.Whenever atraffic source needs a route to a destination,it broadcastsroute request packets(RQ)across the network.Rather than simplyflooding the RQ packets,we adopt the probabilisticbroadcast scheme explored in[30]combined with the MAClayer utilisation.When a nodefirst receives a packet,with probability it broadcasts the packet to its neighbours,andwith probability it discards the packet.The probabilityvalue is calculated as(6) where()is the coefficient.This broadcast scheme helps to discover new routes avoiding congestion areas,but atthe cost of missing potential routes to the destination. During the course offlooding RQ packets to the destination ,the intermediate node receiving a RQ packetfirst sets up reverse paths to the source by recording the source addressand the previous hop node in the message cache.If a validroute to the destination is available,that is,there is at least one link associated with the pheromone trail greater than the lower pheromone bound,the intermediate node generates a route reply(RP).The RP is routed back to the source via the reverse paths.Otherwise,the RQ is rebroadcast.Other than just establishing a single forward path,whenthe destination node receives RQs it will send a RP to allthe neighbours from which it sees a RQ.In order to maintain multiple loop-free paths at each intermediate node,node(b) Path Reinforcement(c) Local Repair(a) Initial Pheromone Setup Fig.2.Illustrating Working Mechanism of EARA-QoSmust record all new forward paths that possess the latest sequence number but hold a lower hop-count in its routing table,and also send a RP to all the neighbours from which it saw a RQ.During the course of the RP tracking back to the source,an initial pheromone value is assigned to the corresponding neighbour node,which indicates a valid route to the destination.This process is illustrated in Figure2(a).D.Route ReinforcementAfter the destination node receives the data traffic sent by the source node,it begins to reinforce some good neighbour(s)in order to“pull”more data traffic through the good path(s)by sending reinforcement signal packets(RS) whenever it detects new good paths.When node receives a RS,it knows it has an outgoing link toward the destination ,which is currently deemed a good path.Subsequently, node updates the corresponding pheromone table entry with the value and forwards a RS packet to(at least one) selected neighbour locally based on its message cache,e.g.the neighbour(s)that saw the least hops of the incoming packets. The amount of the pheromone used to positively rein-force the previous hop neighbour is computed as follows.If the RS packet is sent by the destination to node,then is calculated using the upper bound pheromone value ,(7) If the RS packet is sent by an intermediate node towards node,the is calculated using the current largest pheromone value max()in node with the next hop to the destination in the pheromone table,max(8) where,and are parameters that control the relative weight of the relative source hop distance,the rel-ative packet number and the local queue heuristic. Incorporating the congestion-measuring metric into the reinforcement can lead data traffic to avoid the congestion areas.The relative source hop distance is calculated as follows:(9) where is the shortest hop distance from the source to the current node through node,and is the shortest hop distance from to.This parameter is used to ensure that paths with shorter hop distance from the source node to the current node are reinforced with more pheromone.The relative packet number is calculated as follows:(10) where is the number of incoming packets from neighbour to the destination,and is the total number of incomingpackets towards the destination.This parameter is used to indicate that the data forwarding capacity of a link also affects the reinforcement.The more data arrives,the stronger reinforcement is generated for the corresponding link.On receiving the RS from a neighbour,node needs to positively increase the pheromone of the link towards node.If the sequence number in the RS is greater than the one recorded in the pheromone table,node updates its corresponding pheromone with the value of carried on the RS:(11) If the sequence number is equal to the current one,then:ifotherwise(12)If the sequence number in RS is less than the current one in the pheromone table,then this RS is just discarded.Node also has to decide to reinforce(at least)one of its neighbours by sending the RS message based on its own message cache.This process will continue until reaching the source node.As a result of this reinforcement,good quality routes emerge,which is illustrated in Figure2(b).The same procedure can apply to any intermediate node to perform local link error repair as long as it has pheromone value that is greater than the lower bound.For instance,if an intermediate node detects a link failure from one of its upstream links, it can apply the reinforcement rules to discover an alternative path as shown in Figure2(c).There is also an implicit negative reinforcement for the pheromone values.Within every time interval,if there is no data towards a neighbour node,its corresponding pheromone value decays by a factor as follows:(13)E.Local Foraging AntsIn a dynamic network like MANET,the changes of the net-work topology create chances for new good paths to emerge.In order to make use of this phenomenon,this algorithm launcheslocal foraging ants(LFA)with a time interval to locallysearch for new routes whenever all the pheromone trails of a node towards some destination drop below the threshold.The LFA will take a random walk from its original node. During the course of its walk,if the LFA detects congestionaround a node(the average channel utilisation is greaterthan a predefined threshold value),then the LFA dies to avoid increasingly use the wireless medium.Otherwise,theLFA pushes the address of the nodes that it has travelledinto its memory stack.To avoid forming of loops,LFA will not choose to travel to the node that is already in.Before reaching the maximum hop,if LFA canfind a node with pheromone trails greater than and the hop distanceto destination not greater than the one from its original nest,itreturns to its’nest’following its memory stack and updates the corresponding paths with.Otherwise,it simply dies.F.Local Connectivity ManagementNodes maintain their local connectivity in two ways.When-ever a node receives a packet from a neighbour,it updates its local connectivity information to ensure that it includes thisneighbour.In the event that a node has not sent any packets toits neighbours within a time interval,it has to broadcast a HELLO packet to its neighbours.Failure to receive packetsfrom the neighbourhood in indicates changes in the local connectivity.If HELLO packets are not received from the nexthop along an active path,the node that uses that next hop issent notification of link failure.In case of a route failure occurring at node,cannot for-ward a data packet to the next hop for the intended destination .Node sends a RS message that sets ROUTE RERR tag to inform upstream nodes of the link failure.This RS signalassigns to the corresponding links the lower bound.Here, RS plays the role of an explicit negative feedback signal to negatively reinforce the upstream nodes along the failure path. This negative feedback avoids causing buffer overflow due to caching on-flight packets from upstream nodes. Moreover,the use of HELLO packets can also help to ensure that only nodes with bidirectional connectivity are deemed as neighbours.For this purpose,the HELLO packet sent by a node has an option to list the nodes from which it has heard HELLO packets,and nodes that receive the HELLO check to ensure that it uses only routes to neighbours that have sent HELLO packets.G.The QoS Provision SchemeThis section describes a lightweight approach to DiffServ. The basic idea is to classifyflows into a predefined set of service classes by their relative delay bounds.Admission control only works at the source node.There is no session orflow state information maintained at intermediate nodes. Once a realtime session is admitted,its packets are marked as RT(realtime service)and otherwise they are considered as best-effort bulk packets.As depicted in Figure3,each of these traffic classes is buffered in a logically separate queue.A simple novel queuing strategy,based on the token bucket scheme,provides high priority to realtime traffic,and also protects the lower-priority traffic from starvation.No absolute bandwidth guarantees are provided in this scheme.We explain this queuing strategy and its novelty below.The queues are scheduled according to a token bucket scheme.In this scheme,prioritisation is achieved with token balancing.Each traffic class has a balance of tokens,and the class with higher balance has a higher priority when dequeuing the next packet for transmission.For each transmission of a packet of class,an amount of tokens is subtracted from the class’token balance and an equal fraction thereof is added to every other class’balance such that the sum of all tokens is always the same.The weight value reflects the delay sensitivity assigned to the different classes.A higher weight value corresponds to a lower delay sensitivity.The size of the token balance together with the value determines the maximal length of a burst of traffic from one class.In this scheme,as long as the amount of delay-sensitive traffic does not grow too large,it is forwarded as quickly as possible,and if it does grow too large,starvation of other traffic classes is prevented.Setting the upper bound of a class’token balance depending on its delay-sensitivity enables further tuning of the describedmethod.Fig.3.Overview of Service Differentiation SchemeIn this packet scheduling scheme,routing protocol pack-ets are given unconditional priority before other packets. Moreover,realtime applications normally have stringent delay bounds for their traffic.This means that packets arriving too late are useless.From the application’s point of view,there is no difference between late and lost packets.This implies that it is actually useless to forward realtime packets that stay in a router for more than a threshold amount of time,because they will be discarded at the destination anyway.Dropping those packets instead has the advantage of reducing the load in the network.To our knowledge,this service classification based queuing scheme is the simplest implemented QoS provisioning technique designed exclusively for MANETs so far.V.C HARACTERISTICS OF THE A LGORITHMThis proposed protocol,implementing the cross-layer design concept,exhibits some properties that show itsfitness as a solution for mobile ad hoc networks:Loop-freeness:during the route discovery phase,the nodes record the unique sequence number of RP packets.。

qos实验报告

qos实验报告

竭诚为您提供优质文档/双击可除qos实验报告篇一:Qos队列实验报告高级计算机网络基础实验报告实验三服务质量(qos)组长:王大兴指导老师:袁华吴文波周静刘浩深李苏璇20XX-1-5目录一、实验背景和目的-----------------------------------------3二、实验环境2.1实验设备----------------------------------------------------32.2实验拓扑----------------------------------------------------3三、实验原理3.1锐捷交换机服务质量原理3.1.1分类classifying----------------------------------------43.1.2策略policing-------------------------------------------83.1.3标记marking--------------------------------------------93.1.4队列queueing-------------------------------------------93.1.5调度scheduling----------------------------------------1 1四、测试结果分析4.1交换机的基本配置--------------------------------------------154.2qo s的相关配置----------------------------------------------164.3验证配置----------------------------------------------------184.4完成后的全部配置检查----------------------------------------20五、思考与分析--------------------------------------------21六、总结-------------------------------------------------22一、实验背景和目的qos(qualityofservice,服务质量)是指一个网络能够利用各种各样的技术向选定的网络通信提供更好的服务的能力。

QoS基础理论知识详解

QoS基础理论知识详解

QoS基础理论知识详解01、QOS产生的背景网络的普及和业务的多样化使得互联网流量激增,从而产生网络拥塞,增加转发时延,严重时还会产生丢包,导致业务质量下降甚至不可用。

所以,要在网络上开展这些实时性业务,就必须解决网络拥塞问题。

解决网络拥塞的最好的办法是增加网络的带宽,但从运营、维护的成本考虑,这是不现实的,最有效的解决方案就是应用一个“有保证”的策略对网络流量进行管理。

QoS技术就是在这种背景下发展起来的。

QoS( Quality of Service)即服务质量,其目的是针对各种业务的不同需求,为其提供端到端的服务质量保证。

QoS是有效利用网络资源的工具,它允许不同的流量不平等的竞争网络资源,语音、视频和重要的数据应用在网络设备中可以优先得到服务。

QoS技术在当今的互联网中应用越来越多,其作用越来越重要。

02、QoS服务模型1、Best-Effort服务模型Best-Effort (尽力而为)是最简单的QoS服务模型,用户可以在任何时候,发出任意数量的报文,而且不需要通知网络。

提供Best-Effort服务时,网络尽最大的可能来发送报文,但对时延、丢包率等性能不提供任何保证。

Best-Effort服务模型适用于对时延、丢包率等性能要求不高的业务,是现在In ternet的缺省服务模型,它适用于绝大多数网络应用,如FTP E-Mail等。

2、I ntServ服务模型IntServ(综合服务)模型是指用户在发送报文前,需要通过信令(Signaling) 向网络描述自己的流量参数,申请特定的QoS服务。

网络根据流量参数,预留资源以承诺满足该请求。

在收到确认信息,确定网络已经为这个应用程序的报文预留了资源后,用户才开始发送报文用户发送的报文应该控制在流量参数描述的范围内。

网络节点需要为每个流维护一个状态,并基于这个状态执行相应的QoS动作,来满足对用户的承诺。

IntServ模型使用了RSVP(Resource Reservation Protocol 协议作为信令,在一条已知路径的网络拓扑上预留带宽、优先级等资源,路径沿途的各网元必须为每个要求服务质量保证的数据流预留想要的资源,通过RSVP信息的预留,各网元可以判断是否有足够的资源可以使用。

5G(NR)网络QoS流重新映射

5G(NR)网络QoS流重新映射

5G(NR)网络中经常会遇到(因切换)目标gNB与源gNB映射策略不同,或gNB将新QoS流移走仅剩默认承载的情况;此时用户面QoS Flow与无线承载DRB间就需要重新进行映射。

特别是5G在开启预处理后原承载中的数据QoS流仍在(旧路由中)等待传输,而映射发生了变化;这部分数据量很大也经常出现,网络和终端对QoS流重新映射从以下进行了定义。

一、重新映射规则在旧承载包含来自该QoS流的数据包时,数据包就会同时从旧承载和新承载到达接收方;此时,保留的旧DRB数据按顺序在新DRB交付缓冲,缓冲可在接收器或发射器中进行。

1.1发送器缓冲依赖原则:新承载上的新数据传输仅在旧承载上已传输来自重新定位的QoS流的所有数据包之后才开始。

它对接收器是透明的,但需要发送器缓冲来自重新定位的QoS 流的新数据1.2.接收器缓冲依赖原则:一旦来自旧承载上重新定位的QoS流的所有数据包已被接收并按顺序交付给上层,来自新承载的新数据仅被交付给上层。

它对发送器是透明的,但需要接收器缓冲来自QoS 流的新数据。

二、终端对QoS重映射处理为了最小化对终端(UE)缓冲要求,在下行链路中使用发射器(即gNB)中的缓冲,同时使用接收器(即gNB)中的缓冲在上行链路。

为帮助gNB确认来自搬迁的所有数据QoS流已在旧承载上发送,引入了结束标记;结束标记在更新映射规则之后总是由UE在旧承载上传输。

2.1 下行QoS重定位下行链路中QoS流(见图1)重定位中最初映射到RB1的QoS流A与QoS流B一起重新映射到RB2(图中Step1)。

更新映射规则后来自QoS流A的新数据只要RB1包含来自QoS流程A(图中Step2)。

一旦RB1没有来自QoS流A的剩余数据,可以开始从RB2上的QoS流A传送数据(图中Step3)。

图1.下行QoS重定位(映射)示意图2.2 上行QoS重定位上行链路中QoS流(见图2)重定位中QoS流A最初与QoS 一起映射到RB1流B被重新映射到RB2(图中Step1)。

Fundamental QoS Routing Experiment基本的QS路由实验 PPT资料共31页

Fundamental QoS Routing Experiment基本的QS路由实验 PPT资料共31页
• To replace the Dijkstra algorithm using BellmanFord constrained path computation algorithm: it computes constrained min hop paths to all destinations at each node based on topology map
Find:
- a min cost (typically min hop) path which satisfies such constraints
- if no feasible path found, reject the connection
Example of QoS Routing
2 Hop Path --> Fails (Total delay=55 > 25 and Min BW=20 < 30) 3 Hop Path --> Succeeds (Total delay=24 < 25, Min BW=90 > 30) 5 Hop Path --> Do not consider, although (Total Delay = 16 < 25,
• Simulation platform (UCLA) : PARSEC wired network simulation (QualNet)
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21 50 Km 22
23
15
  1. 1、下载文档前请自行甄别文档内容的完整性,平台不提供额外的编辑、内容补充、找答案等附加服务。
  2. 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
  3. 3、如文档侵犯您的权益,请联系客服反馈,我们会尽快为您处理(人工客服工作时间:9:00-18:30)。
• 36 node, highly connected network • Trunk capacity = 15Mbps • Non uniform traffic requirement • Two routing strategies are compared:
– Minhop routing (no CAC) – QoS routing
- end-to-end delay, - available buffer size, - available bandwidth
Bellman-Ford Algorithm (with delay)
Bellman Equation : Dih+1 =min[d(i ,j) + Dhj]
1
2 10 4
With QoS routing:
– optimal route; “focused congestion” avoidance – efficient Call Admission Control (at the source) – efficient bandwidth allocation (per traffic class) – resource renegotiation easier
• Packet forwarding: (a) source routing (per flow) (b) MPLS (per class)
Application I: IP Telephony
• M-CAC at source; no bandwidth reservation along path
– However, B/F generates solutions by increasing hop distance; thus, the first found feasible solution is “hop” optimal (ie, min hop)
• Polynomial performance for most common sets of MC (multiple constraints e.g. bandwidth and delay )
2) Link State Update - describes sender’s cost to its neighbors
3) Link State Ack. - acknowledges Link State Update
4) Database description - lets nodes determine who has the most recent link state information
35
QoS Simulator: Voice Source Modeling
Voice connection requests arrive according to a Poisson process, or at fixed intervals Once a connection is established, the voice source is modeled as 2 state Markov chain
• Call Acceptance Control (CAC)
• Packet Forwarding: source route or MPLS
OSPF Overview
5 Message Types
1) “Hello” - lets a node know who the neighbors are
QoS Routing and Forwarding
2019
Benefits of QoS Routing
Without QoS routing:
– must probe path & backtrack; non optimal path, control traffic and processing OH, latency

TALK

SILENCE
1/ = 352 ms 1/ = 650 ms 1 voice packet every 20ms during talk state
Simulation Parameters
10 Minute Simulation Runs Each voice connection lasts 3 minutes OSPF updates are generated every 2 seconds (30 minute OSPF update interval in Minhop scheme) New voice connections generated with fixed interarrival (150 ms) Measurements are in Steady-state (after 3 minutes) 100 msec delay threshold 3 Mbit/sec bandwidth margin on each trunk The candidate source destination pairs are : (8,20),(0,34),(3,32), (4,32), (5,32), (10,32), (16, 32)
• To replace the Dijkstra algorithm using BellmanFord constrained path computation algorithm: it computes constrained min hop paths to all destinations at each node based on topology map
Multiple Constraints QoS Routing
Given:
- a (real time) connection request with specified QoS requirements (e.g., Bdw, Delay, Jitter, packet loss, path reliability, etc)
Implementation of OSPF in QoS Simulator
Link State Update is sent every 2 seconds No ack is generated for Link State Updates Link State Update may include (for example):
CAC and Packet Forwarding
• CAC: if feasible path not found, call is rejected; alternatively, source is notified of constraint violation, and can resubmit with relaxed constraint (call renegotiation)
Link State Update is sent every 30 minutes or upon a change in a cost of a path
Link State Update is the only OSPF message which is acknowledged
Routers on the same LAN use “Designated Router” scheme
1
12 42
3 3 25
D21=1
D41=00
D11=0 1 1 3
2
4
one hop
D31=3 D51=00
3
5
Dhi
D
D12=0 1
1
D22=1 2
10
D42=11 4
two hops
1 3
D32=22 D52=5
3
5
D23=1
D43=7
D13=0 1 11 3
2
4
three hops
2
D33=22 D53=4
5) Link State Request - requests link state information
OSPF Overview (cont)
“Link State Update Flooding”1A2
C
1
B
2
2
3
E
3
D
OSPF Overview (cont)
“Hello” message is sent every 10 seconds and only between neighboring routers
Min BW = 90 > 30)
A B
Constraints: Delay (D) <= 25, Available BW >= 30 We look for feasible path with least number of hops
The Components of QoS Routing
– OSPF (Open Shortest Path First): for intra-AS routing – is a link-state protocol that uses flooding of link state
information and a Dijkstra least cost path algorithm
- Queue size of each outgoing queue (averaged over 10s sliding window)
- Throughput on each outgoing link (averaged over 10s sliding window)
- Total bandwidth (capacity of the link) Source router can use above information to calculate
相关文档
最新文档