多媒体传感器网络中服务感知的公平调度算法

针对多媒体传感器网络中基于异常事件驱动的服务模式和基于用户查询驱动的服务模式,分析不同服务的流量模式,提出一种服务感知的公平调度策略,采用基于流量预测的动态公平缓冲共享机制和速率分配算法实现2类数据QoS的公平保障。仿真实验表明,该算法在传输延迟和成功到达率方面实现了公平性目标。     

DiffServ网络中基于流量负载的动态带宽分配

在DiffServ网络中,流量以聚集类的形式存在,聚集类中的流量负载是随时间不断地发生动态变化的.当不同聚集类中的流量负载与调度算法(如WFQ)为其分配的资源(如带宽)不成比例时,即使两个聚集类的优先级相同,它们中的数据包也会得到不公平的待遇.为此,DiffServ网络中面向公平的动态带宽分配引起了广泛的研究.本文中为了实现公平的带宽分配,提出了一种基于流量负载的动态带宽分配的方法,其中在动态计算各个聚集类应分得的新带宽时主要考虑了当前分得的带宽和聚集类的队列长度增量这两个因素.仿真实验结果说明了该方法的有效性.     

DTBF模型的流量负载均衡研究与实现

针对目前网络工程中负载优化困难的问题,基于令牌调度方法提出了一种改进的动态令牌分配调度模型DTBF,实现了实时流的流量整形,推导并设计了动态分配令牌的优化算法以解决逻辑链路间的负载均衡问题。实验分析和工程实现结果表明,此流量调度方法能有效地对链路间进行流量负载均衡,显著提高带宽利用率,用户公平性良好。     

基于流量特征的流调度策略研究综述

软件定义网络将网络的数据层和控制层相分离,具有可编程性强和全局网络视图的优点,这一优点被越来越多的应用于数据中心网络流调度中。然而,数据中心网络中大象流和老鼠流共存的流量特征是流调度技术的一大挑战。对基于流量特征的流调度策略进行了综述,首先梳理了基于软件定义网络的数据中心网络的理论基础,然后对大象流、老鼠流、大象流与老鼠流三个方面的流调度策略进行了分析和总结,并探讨了相比于传统的流调度技术,在软件定义网络架构下基于流量特征的流调度策略的优势。最后针对目前基于流量特征的流调度技术面临的若干主要问题进行了讨论,指出了下一步的研究方向。     

用每流调度和基于路径的汇集调度实现MPLS服务质量:试验比较研究

本文的主要工作在于：1)给出了对于最坏情况下延迟，路径汇集调度优于每流调度的条件；2)通过实验，分析了两种方法在最坏延迟．平均延迟，延迟抖动．公平性等方面的性能差异；3)最后，提出了用基于路径的汇集实现服务质量的一些原则．本文的结果表明，在一定的条件下，基于路径的汇集调度可以实现优于每流调度的最坏情况延迟和延迟抖动；在平均性能上，基于路径的汇集调度没有明显的优势并且在一定程度上牺牲了公平性。     

一种适用突发流量的数据中心网络流调度策略

云数据中心网络的流调度问题是当下的一个研究热点.比较具有实用性的流调度是不假设流信息预先可知,但目前这类流调度方案在流量突发时的表现并不理想.提出了一种针对流量突发情况的流调度方案,通过将每流排队与多级反馈队列调度相结合,实现了一个基于流隔离的多级调度方案FISH,解决了流量突发情况下不同流的排队竞争问题.实验结果表明,该方案性能稳定,可以将小流完成时间降低8.6%以上.     

一种支持DiffServ模型的全分布式调度算法

调度算法设计对于网络路由设备实现区分服务(DiffServ)模型的单跳行为(per hop behavior,简称PHB)至关重要.现有支持DiffServ模型的调度算法普遍基于输出排队(output queued,简称OQ)或是输入排队(input queued,简称IQ)交换结构进行设计,均无法在高速环境下提供高性能的调度.基于联合输入/交叉节点排队(combinedinput-crosspoint-queued,简称CICQ)交换结构提出一种支持DiffServ模型的全分布式调度算法DDSS (distributed DiffServ supporting scheduling),并通过理论分析对其公平性进行了验证.DDSS算法采用基于预约带宽的逐级流量控制机制实现所有预约带宽在快速转发(expedited forwarding,简称EF)业务与确保转发(assured forwarding,简称AF)业务之间的分配,采用优先级调度机制为EF业务提供低延迟服务,算法复杂度为O(log N).仿真结果表明,DDSS算法具有良好的时延性能和公平特性,与现有算法相比,能够更好地支持DiffServ模型.     

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.     

Overlay网络下的超算中心间广域网流量调度研究

广域网上数据中心间的流量互通受复杂互联网环境的影响,跨运营商ISP之间的流量调度对网络传输速率和网络传输延迟影响很大,简单网络架构下的传统流量调度方案已经不能满足迅速增长的网络流量,严重影响了传输服务的质量.本文以国家高性能计算环境为研究背景,提出一个新的互联网环境多超算数据中心流量调度模型,利用Overlay网络构建一个流量调度完全可控的虚拟网络,通过改进底层网络协议和路由更新算法,在端到端节点间使用转发节点进行流量调度.本文通过实际超算环境进行实验,结果表明在跨运营商网络环境下使用基于Overlay网络的流量调度,可以明显降低网络传输延迟,提高传输带宽.     

漏桶模型下GPS调度系统的性能分析

着重分析了在数据流分别由线性漏桶和分形漏桶模型进行约束和整形的情况下，GPS(Generalized Processor Sharing)通用处理器共享调度系统的排队性能，给出了最大队长和最大时延的估算方法，并将理论分析与实验结果做了一定对比．文章分析指出，对UDP流和聚集程度不高的TCP流，用线性漏桶模型是有效的；而对于聚集程度较高的TCP流，用分形漏桶模型来描述其流量则比较合适．     

Hardware design and implementation of packet fair queuing algorithms for the quality of service support in the high-speed internet

The increasing amount of real-time traffic carried over the Internet requires end-to-end quality of service (QoS) support. To this end, the QoS Schedulers, that are implemented in routers, assign the available bandwidth resources to packet flows according to their respective allocated rates. Packet Fair Queuing (PFQ) schedulers can provide fair service and low end-to-end delay bound to the traffic flows. However, they have higher implementation complexity compared to other algorithms, because of the requirements of tracking the system state, and searching for the packet to get service among all flows, that are queued at the outgoing interface. QoS scheduling is a data plane functionality, which requires hardware implementation for high speed router interfaces. The previous works on hardware implementation of PFQ schedulers are specific to certain algorithms, and they do not provide any results on real hardware platforms. In this paper, we present a general hardware design framework for PFQ schedulers, and apply this framework to the WF²Q+ PFQ algorithm to demonstrate its properties. We carry out the entire implementation of the WF²Q+ algorithm on an FPGA, and evaluate its performance with real traffic flows. In addition, we implement WFQ as a second PFQ algorithm to demonstrate the generality of the framework.     

Tight end-to-end per-flow delay bounds in FIFO multiplexing sink-tree networks

Aggregate scheduling has been proposed as a solution for achieving scalability in large-size networks. However, in order to enable the provisioning of real-time services, such as video delivery or voice conversations, in aggregate scheduling networks, end-to-end delay bounds for single flows are required. In this paper, we derive per-flow end-to-end delay bounds in aggregate scheduling networks in which per-egress (or sink-tree) aggregation is in place, and flows traffic is aggregated according to a FIFO policy. The derivation process is based on Network Calculus, which is suitably extended to this purpose. We show that the bound is tight by deriving the scenario in which it is attained. A tight delay bound can be employed for a variety of purposes: for example, devising optimal aggregation criteria and rate provisioning policies based on pre-specified flow delay bounds.     

Deterministic end-to-end delay guarantees with rate controlled EDF scheduling

Quality of Service (QoS) in terms of end-to-end delay guarantees to real-time applications is an important issue in emerging broadband packet networks. Earliest Deadline First (EDF) scheduling, in conjunction with per-hop traffic shaping (jointly called Rate Controlled EDF or RC-EDF) has been recognised as an effective means of end-to-end deterministic delay provisioning. This paper addresses the issue of identifying RC-EDF shaping parameters that realize maximal network utilizations. We first prove that finding “optimal” shapers is in general infeasible, and then propose a heuristic choice derived from the flow’s hop-length. Our choice varies gracefully between known optimal settings for the limiting values of the hop-length, and outperforms shaper selections proposed previously in the literature.     

无线多跳网QoS性能统计性边界的研究

为保证无线多跳网的服务质量（QoS）,需要求解其性能边界。基于统计型流量包络建立了无线多跳网的数据流传输模型,在此模型的基础上利用统计网络演算理论推导了无线多跳网单节点的时延统计性边界、端到端的时延统计性边界以及端到端数据积压统计性边界。仿真实验结果表明,不同数据流的测量值都在数值计算的边界范围之内,表明基于统计网络演算理论的无线多跳网QoS边界模型具有较好的性能。     

End-to-end QoS guarantees for a network based on Latency-Rate Max–Min service curve

Recently, a number of studies have been made based on the concept of Route Interference to provide deterministic end-to-end quality of service (QoS) guarantees. Nonetheless, these studies tend to confine to a simple scheduling scheme and study the traffic in a single-class environment or the highest priority traffic in a multi-class environment. This is rather restrictive. In this paper, we propose a new general service scheme to service flows. This scheme is represented by a Latency-Rate Max–Min service curve (LRMMSC). Subsequently, for a network of LRMMSC, we prove the existence of tight bounds on end-to-end queuing delay and buffer size needed for loss-free packet delivery, provided that all flows obey a given source rate condition in the form of their route interference. Our approach has two salient features: (1) the general nature of the concept of service curve enables the service scheme to be implemented by many well-known scheduling disciplines, (2) the general network model adopted with no constraints on the manner of packet queuing makes the results applicable to many complex networks. In addition, we have also derived a concise expression of end-to-end delay bound that depends only on the service offered to the buffers containing the considered flow. This is very useful in practice as the expression is simple and requires minimum amount of information input. Simulation experiments are conducted to verify the LRMMSC model. The analytical and simulation results exhibit close resemblance. In addition, the advantage of LRMMSC scheme in providing maximum end-to-end delay is also demonstrated.     

基于EDF调度算法的端到端延迟保证方法

EDF(EarliestDeadlineFirst)是一种高效的调度算法。为了将其应用于提供端到端延迟保证,提出了一种新的算法JT-EDF(JitterTunableEDF),并证明了所有的端到端EDF调度算法都可以在相同的条件下保证相同的端到端延迟界。     

基于统计移位排序结构的高速路由器公平队列调度算法实现

高速化和多媒体化是未来网络的主要发展方向,为了给用户提供可靠的端到端服务质量保证,通常需要在网络的中继节点上引入基于流的队列调度机制。WF^2Q＋队列调度算法即是一种性能优异同时又易于实现的公平队列调度算法。文中提出了一种基于统计移位排序结构的WF^2Q＋算法高速硬件实现方法,该方法充分利用队列的统计信息,以相对较少的硬件资源实现了统计意义上的快速完全排序。FPGA实现的结果表明,该结构可以应用于端口速率为OC－48的高速IP路由器上。     

Quantum-Based Earliest Deadline First Scheduling for Multiservices

Latency-rate (LR) schedulers have shown their ability in providing fair and weighted sharing of bandwidth with an upper bound on delivery latency of packets while earliest departure first (EDF) schedulers have shown their ability in providing LR-decoupled service whereby the delivery latency of packets is not bounded by the reserved rate. However, EDF schedulers require traffic shapers to ensure flow protection. We propose quantum-based earliest deadline first scheduling (QEDF), a quantum-based scheduler that provides flow protection, throughput guarantee and delay bound guarantee for flows that require LR-coupled and LR-decoupled types of reservations. It classifies flows into time-critical (TC), jitter-sensitive (JS), and rate-based (RB) classes and uses a quality-of-service forwarding rule to determine the next packet to be serviced by the scheduler. It provides nonpreemptive priority service to TC queues. This allows LR-decoupled reservation for flows that have a low rate and intolerable delay. Packets from JS queues can be delayed by other packets if forwarding the latter will not result in the former missing its deadline. As a quantum-based scheduler, the QEDF scheduler provides throughput guarantees for RB queues. We present both analytical and simulation results of QEDF, whereby we evaluated QEDF in its deployment as a single-class as well as a multiservice scheduler     

基于域内全局流标签的可扩展QoS模型

针对互联网现有服务质量(QoS:quality of service)模型的扩展性差、端到端延时高等问题,提出了基于域内全局流标签的QoS保障模型。该模型以WFQ队列调度模型为基础,采用域内全局流标签进行资源预留和路由转发,能够实现灵活的服务质量保证,具有更强的可扩展性。在此基础上,利用网络微积分理论对所提模型进行了端到端延时分析,给出了该模型端到端服务曲线和延时上界的表示式。理论分析和数值实验表明基于域内全局流标签的QoS保障模型具有比现有模型更低的端到端延时上界。