基于差分队列服务（DQS）的融合网络服务质量保障研究
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摘要
宽带无线网络的移动化和移动通信网络的宽带化进程推动了基于IP的融合网络的演进。支持多种接入技术、提供多样化业务、无时无处不在等已成为下一代宽带融合网络的重要特征。然而服务质量(QoS)保障在融合网络里面临更新更大的挑战。例如，各种接入技术并存使端到端QoS保障更加复杂，多样化业务的发展要求融合网络提供混合QoS流的支持和宽泛的时延保障，实时业务所占比重的增大及其时延敏感性使数据包时延超时概率成为融合网络QoS性能的一个重要指标。此外，无线网络资源的有限性使通过提供超额服务实现QoS保障的方案不再适用于融合网络。因此，围绕融合网络的网络特性和业务特性研究QoS保障具有重要的意义。
传统的QoS模型包括综合服务(IntServ)和区分服务(DiffServ)以及它们的变体。这些模型除了很难在可扩展性和QoS服务粒度两个方面达到均衡外，在融合网络的QoS保障方面也面临一系列的问题。近年来出现的一种基于数据包粒度的差分队列服务(DQS)用于解决有线网络的可扩展性和QoS服务粒度均衡问题，后来被扩展到无线网络。其主要服务规则包括：DQS要求每个数据包明确携带其QoS要求，如时延要求、丢包优选标志等。DQS路由器根据数据包的QoS要求决定其在缓存队列里的位置，也即决定了数据包调度的顺序和丢弃优先级。DQS可以根据端到端路径提供区分的QoS和支持混合QoS流和范围广泛的时延要求。所以DQS是一种适用于融合网络的QoS模型。由于DQS作为一种端到端QoS模型仍处于初始研究阶段，如何利用DQS实现融合网络的QoS保障仍有待进一步研究。其中包括基于DQS的资源分配、QoS保障的接纳控制以及如何实现端到端自适应QoS保障等。
本文首先介绍了DQS的基本原理、关键技术和实现QoS保障尚需研究的问题，在此基础上研究了DQS基于QoS保障的资源分配、基于网络容量动态变化的接纳控制和建立端到端QoS性能模型，最后提出了一种基于DQS的自适应端到端QoS保障方案。本文的具体研究成果和创新如下：
1)根据时延要求建立业务流模型和用服务能力曲线表示动态的网络容量。传统的网络分析方法一般按流或类的粒度建立数据流的业务模型。本文首次按数据包的时延要求建立业务流模型。按数据包的时延要求将到达的业务划分为有限个数据流，具有相同时延要求的业务看作一个数据流并用一个独立的业务模型表示。此方法可灵活描述混合QoS流以及支持宽泛的时延要求。此外，基于中心极限定理建立了链路容量动态变化的无线链路随机服务能力曲线。此方法将无线链路的信道容量、信噪比、移动速率等网络下层的参数映射为平均带宽、带宽变量和时间段这三个网络层服务能力参数，既降低了网络分析过程的复杂性又反映了无线链路的带宽时变特性。
2)研究了基于DQS的融合网络单个节点实现QoS保障的问题，包括：
a) QoS保障的带宽和缓存资源分配：针对多个分形布朗运动(FBM)业务模型、对应的时延要求研究了网络容量不变时的独立分配资源和全局资源共享这两种方式的带宽和缓存需求以及混合业务时的带宽和缓存需求。
b)网络容量动态变化的QoS保障接纳控制:建立了网络容量动态变化的QoS性能模型，提出了以时延超时概率为阈值的QoS保障接纳控制算法，并利用半马尔可夫决策过程(SMDP)优化此接纳控制算法。
3)研究了基于DQS的融合网络多个节点实现QoS保障的问题，包括：
a)以网络演算为基础分析了基于DQS的融合网络端到端QoS性能。首先分析了端到端确定服务的QoS性能。基于此提出一种根据数据流的业务包络率来预留端到端带宽从而控制数据流的端到端时延超时概率的方法，来实现融合网络的端到端QoS保障，接下来推导了基于随机服务的端到端时延超时概率上界。该概率上界既可用于端到端随机QoS保障的性能评估又可用于端到端QoS保障的流量控制，具有重要的理论价值。
b)提出了一种基于DQS的自适应端到端QoS保障方案。根据节点在融合网络中的网络属性，依次提出了动态确定数据包在网关节点、无线网络节点和有线网络节点的时延界的算法。以上所提方案和模型均通过计算机模拟仿真来检验和验证，仿真结果表明，它们均能达到预期的效果。
With the mobile evolution of wireless broadband access networks and the broadband evo-lution of mobile cellular communication networks, the future networks are evolved to IP-basedintegrated networks with heterogeneous access technologies. Support of multiple access tech-nologies, provisioningofvariousapplicationsanywhereanytimeandanyhowthroughanythingwill been the important features of next generation networks. However, QoS provisioning in in-tegrated networks faces novel and serious challenges. For example, end-to-end QoS provision-ing becomes more complex due to various access technologies. The development of variousapplications requires QoS support of mixed flows and a wide range of delay guarantee. Thetime sensitive nature of the increasing real time applications makes delay bound violation prob-abilitybecomeanovelandimportantperformancemetricinmeasuringtheQoSprovisioningforintegrated networks. Furthermore, QoS over-provisioning is no longer suitable for integratednetworks due to the wireless resources constraint. Consequently, the study on the end-to-endQoS provisioning in such kind of networks is meaningful.
Traditional QoS schemes include IntServ and DiffSev as well as their variants. However,besides that they are not able to balance well between scalability and QoS granularity, they alsoface a series of problems in QoS provisioning in integrated networks with the novel features ofintegrated networks mentioned above. Differentiated Queueing Service (DQS) was proposedto balance service granularity and scalability in wired networks initially and then extended towireless networks. The main service disciplines of DQS are as follows: DQS explicitly requireseach packet to carry its QoS requirements by itself in terms of end-to-end delay bound andpacket loss preference. Then the routers along the path properly place the arriving packets inthe queue according to their QoS requirements and those of all the already queued packets.Due to its per-packet service granularity, DQS could provide differentiated services accordingto end-to-end path situations and could support a wide range of QoS requirements especiallydelayrequirements, consequentlyitisasuitableQoSschemeforintegratednetworks. However,although DQS was suggested to be an end-to-end QoS scheme, more works on how to provisionQoSwithitinintegratednetworksshouldbedone,includingresourceallocation,QoS-constraintadmission control, how to support end-to-end QoS adaptability and so on.
In the following we firstly overview the service disciplines of DQS, then briefly introducethe key technologies of DQS and the state of the art as well. In the sequel we will study theresource allocation of DQS for QoS provisioning and admission control for DQS with time-varying network capacity as well as end-to-end QoS performance models of DQS. Finally wepropose an adaptive end-to-end QoS provisioning scheme of DQS in integrated networks. Themain contributions are as follows:
1) Input flows are modeled according to their delay requirements and a service capabilitycurve is proposed to represent the dynamic network capacity. Traditional methods on networkanalysis commonly model the Internet traffic in per-flow or per-class granularity. This papermodels the Internet traffic in packet granularity by delay bounds. Arrival traffic is classifiedinto limited data flows according to their delay requirements. Packets with the same delayrequirements are modeled into a traffic flow. This method can flexibly describe mixed QoSflow and support a wide range of delay requirements. We further propose a stochastic servicecapability curve to represent the dynamic wireless link with the center limit theorem. Thismethod can map the parameters of lower layer, such as channel capacity, SINR and mobilerate and so on, into service capability parameters of network layer including mean bandwidth,bandwidth variable and time interval. This method can simple the process of network calculusand reflect the property of time-varying bandwidth of wireless link.
2) Studies on QoS provisioning of DQS with single node, including:
a) Study on bandwidth and buffer allocation for QoS provisioning. We derive the re-quired bandwidth and buffer resources separately for the resource allocation manners ofper-flow dedicated resource allocation and global shared resources with multiple FBM(Fractional Brownian Motion) inputs and their delay requirements as well as constant net-work capacity. We also derive the required bandwidth and buffer resources for mixedtraffic, which include real-time and non-real-time applications.
b) Study on admission control for QoS provisioning with time-varying network capac-ity. We build the QoS performance model and further propose a QoS guaranteed ad-mission control algorithm by using delay bound violation probability deduced above asa main threshold. Then SMDP (Semi-Markov Decision Process) are used to optimal theadmission control policy.
3) Studies on End-to-end QoS provisioning of DQS with multiple nodes, including:
a) Analysisofend-to-endQoSperformanceofDQSwiththetheoryofnetworkcalculus.We firstly analyze the end-to-end QoS performance with deterministic service. A schemethat reserving end-to-end bandwidth according to envelope rate of input flow is proposedfor end-to-end QoS provisioning. Then an upper bound of end-to-end delay bound vio-lation probability is derived with stochastic network calculus and chernoff bounds. Theupper bound could be used to investigate the end-to-end QoS provisioning performanceand be applied to traffic control, thus it has important theoretical value.
b) Proposed an adaptive end-to-end QoS provisioning scheme of DQS in integrated net-works. Weproposedistinctdynamicdelayboundestimationalgorithmsfordifferenttypesof nodes for QoS adaptation in integrated networks.
The above proposals and models are all verification and validation by computer simula-tions. The simulation results show that all of them could achieve the desired results.
传统的QoS模型包括综合服务(IntServ)和区分服务(DiffServ)以及它们的变体。这些模型除了很难在可扩展性和QoS服务粒度两个方面达到均衡外，在融合网络的QoS保障方面也面临一系列的问题。近年来出现的一种基于数据包粒度的差分队列服务(DQS)用于解决有线网络的可扩展性和QoS服务粒度均衡问题，后来被扩展到无线网络。其主要服务规则包括：DQS要求每个数据包明确携带其QoS要求，如时延要求、丢包优选标志等。DQS路由器根据数据包的QoS要求决定其在缓存队列里的位置，也即决定了数据包调度的顺序和丢弃优先级。DQS可以根据端到端路径提供区分的QoS和支持混合QoS流和范围广泛的时延要求。所以DQS是一种适用于融合网络的QoS模型。由于DQS作为一种端到端QoS模型仍处于初始研究阶段，如何利用DQS实现融合网络的QoS保障仍有待进一步研究。其中包括基于DQS的资源分配、QoS保障的接纳控制以及如何实现端到端自适应QoS保障等。
本文首先介绍了DQS的基本原理、关键技术和实现QoS保障尚需研究的问题，在此基础上研究了DQS基于QoS保障的资源分配、基于网络容量动态变化的接纳控制和建立端到端QoS性能模型，最后提出了一种基于DQS的自适应端到端QoS保障方案。本文的具体研究成果和创新如下：
1)根据时延要求建立业务流模型和用服务能力曲线表示动态的网络容量。传统的网络分析方法一般按流或类的粒度建立数据流的业务模型。本文首次按数据包的时延要求建立业务流模型。按数据包的时延要求将到达的业务划分为有限个数据流，具有相同时延要求的业务看作一个数据流并用一个独立的业务模型表示。此方法可灵活描述混合QoS流以及支持宽泛的时延要求。此外，基于中心极限定理建立了链路容量动态变化的无线链路随机服务能力曲线。此方法将无线链路的信道容量、信噪比、移动速率等网络下层的参数映射为平均带宽、带宽变量和时间段这三个网络层服务能力参数，既降低了网络分析过程的复杂性又反映了无线链路的带宽时变特性。
2)研究了基于DQS的融合网络单个节点实现QoS保障的问题，包括：
a) QoS保障的带宽和缓存资源分配：针对多个分形布朗运动(FBM)业务模型、对应的时延要求研究了网络容量不变时的独立分配资源和全局资源共享这两种方式的带宽和缓存需求以及混合业务时的带宽和缓存需求。
b)网络容量动态变化的QoS保障接纳控制:建立了网络容量动态变化的QoS性能模型，提出了以时延超时概率为阈值的QoS保障接纳控制算法，并利用半马尔可夫决策过程(SMDP)优化此接纳控制算法。
3)研究了基于DQS的融合网络多个节点实现QoS保障的问题，包括：
a)以网络演算为基础分析了基于DQS的融合网络端到端QoS性能。首先分析了端到端确定服务的QoS性能。基于此提出一种根据数据流的业务包络率来预留端到端带宽从而控制数据流的端到端时延超时概率的方法，来实现融合网络的端到端QoS保障，接下来推导了基于随机服务的端到端时延超时概率上界。该概率上界既可用于端到端随机QoS保障的性能评估又可用于端到端QoS保障的流量控制，具有重要的理论价值。
b)提出了一种基于DQS的自适应端到端QoS保障方案。根据节点在融合网络中的网络属性，依次提出了动态确定数据包在网关节点、无线网络节点和有线网络节点的时延界的算法。以上所提方案和模型均通过计算机模拟仿真来检验和验证，仿真结果表明，它们均能达到预期的效果。
With the mobile evolution of wireless broadband access networks and the broadband evo-lution of mobile cellular communication networks, the future networks are evolved to IP-basedintegrated networks with heterogeneous access technologies. Support of multiple access tech-nologies, provisioningofvariousapplicationsanywhereanytimeandanyhowthroughanythingwill been the important features of next generation networks. However, QoS provisioning in in-tegrated networks faces novel and serious challenges. For example, end-to-end QoS provision-ing becomes more complex due to various access technologies. The development of variousapplications requires QoS support of mixed flows and a wide range of delay guarantee. Thetime sensitive nature of the increasing real time applications makes delay bound violation prob-abilitybecomeanovelandimportantperformancemetricinmeasuringtheQoSprovisioningforintegrated networks. Furthermore, QoS over-provisioning is no longer suitable for integratednetworks due to the wireless resources constraint. Consequently, the study on the end-to-endQoS provisioning in such kind of networks is meaningful.
Traditional QoS schemes include IntServ and DiffSev as well as their variants. However,besides that they are not able to balance well between scalability and QoS granularity, they alsoface a series of problems in QoS provisioning in integrated networks with the novel features ofintegrated networks mentioned above. Differentiated Queueing Service (DQS) was proposedto balance service granularity and scalability in wired networks initially and then extended towireless networks. The main service disciplines of DQS are as follows: DQS explicitly requireseach packet to carry its QoS requirements by itself in terms of end-to-end delay bound andpacket loss preference. Then the routers along the path properly place the arriving packets inthe queue according to their QoS requirements and those of all the already queued packets.Due to its per-packet service granularity, DQS could provide differentiated services accordingto end-to-end path situations and could support a wide range of QoS requirements especiallydelayrequirements, consequentlyitisasuitableQoSschemeforintegratednetworks. However,although DQS was suggested to be an end-to-end QoS scheme, more works on how to provisionQoSwithitinintegratednetworksshouldbedone,includingresourceallocation,QoS-constraintadmission control, how to support end-to-end QoS adaptability and so on.
In the following we firstly overview the service disciplines of DQS, then briefly introducethe key technologies of DQS and the state of the art as well. In the sequel we will study theresource allocation of DQS for QoS provisioning and admission control for DQS with time-varying network capacity as well as end-to-end QoS performance models of DQS. Finally wepropose an adaptive end-to-end QoS provisioning scheme of DQS in integrated networks. Themain contributions are as follows:
1) Input flows are modeled according to their delay requirements and a service capabilitycurve is proposed to represent the dynamic network capacity. Traditional methods on networkanalysis commonly model the Internet traffic in per-flow or per-class granularity. This papermodels the Internet traffic in packet granularity by delay bounds. Arrival traffic is classifiedinto limited data flows according to their delay requirements. Packets with the same delayrequirements are modeled into a traffic flow. This method can flexibly describe mixed QoSflow and support a wide range of delay requirements. We further propose a stochastic servicecapability curve to represent the dynamic wireless link with the center limit theorem. Thismethod can map the parameters of lower layer, such as channel capacity, SINR and mobilerate and so on, into service capability parameters of network layer including mean bandwidth,bandwidth variable and time interval. This method can simple the process of network calculusand reflect the property of time-varying bandwidth of wireless link.
2) Studies on QoS provisioning of DQS with single node, including:
a) Study on bandwidth and buffer allocation for QoS provisioning. We derive the re-quired bandwidth and buffer resources separately for the resource allocation manners ofper-flow dedicated resource allocation and global shared resources with multiple FBM(Fractional Brownian Motion) inputs and their delay requirements as well as constant net-work capacity. We also derive the required bandwidth and buffer resources for mixedtraffic, which include real-time and non-real-time applications.
b) Study on admission control for QoS provisioning with time-varying network capac-ity. We build the QoS performance model and further propose a QoS guaranteed ad-mission control algorithm by using delay bound violation probability deduced above asa main threshold. Then SMDP (Semi-Markov Decision Process) are used to optimal theadmission control policy.
3) Studies on End-to-end QoS provisioning of DQS with multiple nodes, including:
a) Analysisofend-to-endQoSperformanceofDQSwiththetheoryofnetworkcalculus.We firstly analyze the end-to-end QoS performance with deterministic service. A schemethat reserving end-to-end bandwidth according to envelope rate of input flow is proposedfor end-to-end QoS provisioning. Then an upper bound of end-to-end delay bound vio-lation probability is derived with stochastic network calculus and chernoff bounds. Theupper bound could be used to investigate the end-to-end QoS provisioning performanceand be applied to traffic control, thus it has important theoretical value.
b) Proposed an adaptive end-to-end QoS provisioning scheme of DQS in integrated net-works. Weproposedistinctdynamicdelayboundestimationalgorithmsfordifferenttypesof nodes for QoS adaptation in integrated networks.
The above proposals and models are all verification and validation by computer simula-tions. The simulation results show that all of them could achieve the desired results.
引文
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