基于GMPLS的动态分布式WDM网状网路由选择算法研究

研究了在基于GMPLS的WDM网络中，当节点不具备波长变换能力并且配备有限个光收发器对时，如何为到达的业务请求建立标记交换路径（LSP）的问题。提出一种以跳数和带宽碎片要求为权重，合理分配带宽资源的新算法。仿真结果表明，该算法在保证用户业务可靠性要求的同时，能够更有效地提高全网资源的利用率，并大大降低网络阻塞的可能性。     

多业务网络动态带宽分配算法研究

在多业务网络环境中,面对不同的QoS需求,为不同业务分配合理的带宽资源是提高网络效率的有效保障。探讨了多业务网络环境下的带宽资源管理办法。重点研究了区分业务模型Diffserv中相关队列调度算法的基本原理,并对加权循环算法WRR进行改进。在基于周期测量发送队列的基础上对队列分配权值进行动态调整,使高优先级业务能够得到充分带宽资源保证的同时,对低优先级业务也有最低的传输带宽保证,从而满足多个业务的共同需求。通过NS2仿真和分析表明,经过改进的算法能对多业务环境下的数据传输提供区分服务,并且使得高优先级业务在丢包数和数据延迟方面与低优先级业务相比有明显减少。     

联合资源管理的异构无线网络垂直切换算法

针对资源有限的无线异构网络,关键问题是如何管理稀缺的无线资源(如带宽)来满足服务提供者和享受服务的用户的需求。提出一种联合带宽动态分配,准入控制的垂直切换算法,旨在提高运营商的利益最大化的同时兼顾用户的服务质量。仿真结果表明,该算法可以有效地提高带宽资源的利用率,有效降低阻塞率和掉话率,能够满足不同业务的切换要求,适合异构无线网络的多业务传输。     

WDM网状网络中一种动态多播自适应业务疏导算法

光多播业务需要消耗大量的WDM光网络带宽资源,业务疏导是光多播网络降低业务请求阻塞率和提高带宽资源利用率的有效方法。提出了一种新型光多播疏导节点结构,研究了疏导端口优先的多播业务疏导算法(TGPFA)和新建光树优先的多播业务疏导算法(TCLFA),进而提出了一种能够适应网络资源变化的动态多播业务疏导算法(ADMGA)。结果表明,在网络资源有限的情况下,ADMGA算法能取得较低的请求阻塞率和带宽阻塞率,获得较好的网络性能。     

基于深度学习的流量工程算法研究与应用

随着5G网络的发展和应用,网络中的业务数量呈现出爆发式增长,网络中的带宽资源日趋紧张。为了提高网络资源利用率,并满足用户日益提高的业务服务质量要求,基于软件定义网络(SDN)提出了一种基于深度学习的流量工程算法(DL-TEA)。通过仿真证明该算法不仅能够实时地为业务计算一条高效的路径,同时还能够提升业务的QoS、网络资源利用率,降低网络阻塞率。     

一种WDM-PON系统中基于SLA的动态带宽算法

文章提出了一种基于业务等级协议(SLA)的动态带宽分配算法,该算法根据SLA为光网络单元(ONU)分配带宽权重和相应的优先权,确保了ONU的带宽分配和服务质量,改善了网络的性能,满足了网络业务的QoS要求.最后,通过仿真证明了这种算法的正确性.     

基于网络态势的栅格网多径并行传输算法

栅格网将各种通信资源通过虚拟化技术融合在一起,以统一的网络态势为上层应用提供服务。利用栅格网的特点,提出基于网络态势的多径并行传输算法,将通信业务合理分配在多条并行路径上进行传输,或将多条较低带宽的路径虚拟为一个较高带宽的端到端路径来提供服务,适用于战术通信环境等具有较多低带宽链路的栅格网络,仿真结果表明该算法可大大提高网络吞吐量和资源利用率。     

弹性光网络双重故障下的自适应保护级别算法

为了降低弹性光网络中双链路故障保护下的业务及带宽阻塞率、均衡带宽资源分配,提出了一种双重故障下的自适应保护级别算法。该算法综合考虑传输距离、调制格式等因素,根据链路频谱资源使用状态动态地更新链路惩罚系数,选取最佳路径进行传输,同时根据请求类型及网络空闲资源状态自适应地选择保护方法,为业务提供最大限度的保护。仿真结果表明,在双链路故障下,算法在阻塞率方面取得了较好的性能,同时均衡了网络中各链路上的资源使用。     

SDH环状传输网络中的业务疏导策略研究

本文针对SDH环状传输网络着重讨论了一套称为FCCA和PCCA的业务疏导算法，通过合理分配SDH传输通道承载业务，尽量节省传输资源，提高网络的带宽使用效率。仿真结果显示，网络中的业务流量越均衡，该算法能节约的带宽比例越太。     

IFQ:一种新的ATM网络业务调度算法

本文提出了插空公平公队列（ＩＦＱ）调度算法。由于该方法考虑了ＡＴＭ网络中不同种类连接的特性,能充分利用网络资源。理论分析和仿真实验表明,ＩＦＱ算法能为Ｇ连接提供预约带宽保证和确定的时延上界,满足业务的实时传输要求。同时ＩＦＱ调度算法还具有连接独立性特点,能灵活地分配带宽资源。     

An optimal solution to resource allocation among soft QoS traffic in wireless network

Optimization theory and nonlinear programming method have successfully been applied into wire‐lined networks (e.g., the Internet) in developing efficient resource allocation and congestion control schemes. The resource (e.g., bandwidth) allocation in a communication network has been modeled into an optimization problem: the objective is to maximize the source aggregate utility subject to the network resource constraint. However, for wireless networks, how to allocate the resource among the soft quality of service (QoS) traffic remains an important design challenge. Mathematically, the most difficult comes from the non‐concave utility function of soft QoS traffic in the network utility maximization (NUM) problem. Previous result on this problem has only been able to find its sub‐optimal solution. Facing this challenge, this paper establishes some key theorems to find the optimal solution and then present a complete algorithm called utility‐based allocation for soft QoS to obtain the desired optimal solution. The proposed theorems and algorithm act as designing guidelines for resource allocation of soft QoS traffic in a wireless network, which take into account the total available resource of network, the users’ traffic characteristics, and the users’ channel qualities. By numerical examples, we illustrate the explicit solution procedures.Copyright © 2013 John Wiley & Sons, Ltd.     

基于多门限预留机制的自适应带宽分配算法

针对异构无线网络融合环境提出了一种基于多门限预留机制的自适应带宽分配算法,从而为多业务提供QoS保证。该算法采用多宿主传输机制,通过预设各个网络中不同业务的带宽分配门限,并基于各个网络中不同业务和用户的带宽分配矩阵,根据业务k支持的传输速率等级需求和网络状态的变化,将自适应带宽分配问题转化为一个动态优化问题并采用迭代方法来求解,在得到各个网络中不同业务和用户优化的带宽分配矩阵的同时,在带宽预留门限和网络容量的约束条件下实现网络实时吞吐量的最大化,以提高整个异构网络带宽的利用效率。数值仿真结果显示,所提算法能够支持满足QoS需求的传输速率等级,减小了新用户接入异构网络的阻塞概率,提高了平均用户接入率并将网络吞吐量最大提高40%。     

流量工程中静态路由算法的研究

该文提出了一种应用于流量工程环境中的静态路由算法。考虑当前的网络资源情况,分优先级别在网络中计算并配置标记交换路径(Label Switched Path,LSP),当某一优先级有多条 LSP需要并行配置时,利用遗传算法搜索最优或较优的配置方案,使得网络的链路带宽使用率低于管理员定义的某个限定值,达到合理分布资源的目的。此外,提出了一种改进的 Dijkstra 算法计算 LSP的最短路径。     

面向可重构服务承载网的分域混合承载组调度研究

传统网络技术体系,网络是封闭的、刚性的,无法满足未来网络大量差异化业务的规模化应用,由此提出了面向服务提供的柔性网络技术体系,该体系将传统网络中的用户业务、网络服务和网络基础设施中的紧耦合关系转变为松耦合关系,通过资源分割构建可重构服务承载网实现对业务的服务质量保证。该文分析了服务承载网映射到交换结构的需求,提出分域调度的思想。通过选择关闭部分交叉节点的方法建立了crossbar交换结构分域模型,实现了分域调度的端口分离。提出了支持可重构服务承载网构建的混合承载组调度(HCGS)算法,推导了承载组内SDRR(Smoothed Deficit Round Robin)调度、单个域内基于时间戳的输入端口调度和交叉节点输出端口调度算法,证明了HCGS具有良好的时延性能和最坏公平指数(WFI)公平性。仿真结果表明:在均匀分布的泊松业务源条件下,分域HCGS算法具有更优的时延性能,可保证业务带宽的公平性。在diagonal非均匀允许流量条件下,该算法的吞吐量可达100%。     

Reconfiguration and Dynamic Load Balancing in Broadcast WDM Networks*

In optical WDM networks, an assignment of transceivers to channels implies an allocation of the bandwidth to the various network nodes. Intuition suggests, and our recent study has confirmed, that if the traffic load is not well balanced across the available channels, the result is poor network performance. Hence, the time-varying conditions expected in this type of environment call for mechanisms that periodically adjust the bandwidth allocation to ensure that each channel carries an almost equal share of the corresponding offered load. In this paper we study the problem of dynamic load balancing in broadcast WDM networks by retuning a subset of transceivers in response to changes in the overall traffic pattern. Assuming an existing wavelength assignment and some information regarding the new traffic demands, we present two approaches to obtaining a new wavelength assignment such that (a) the new traffic load is balanced across the channels, and (b) the number of transceivers that need to be retuned is minimized. The latter objective is motivated by the fact that tunable transceivers take a non-negligible amount of time to switch between wavelengths during which parts of the network are unavailable for normal operation. Furthermore, this variation in traffic is expected to take place over larger time scales (i.e., retuning will be a relatively infrequent event), making slowly tunable devices a cost effective solution. Our main contribution is a new approximation algorithm for the load balancing problem that provides for tradeoff selection, using a single parameter, between two conflicting goals, namely, the degree of load balancing and the number of transceivers that need to be retuned. This algorithm leads to a scalable approach to reconfiguring the network since, in addition to providing guarantees in terms of load balancing, the expected number of retunings scales with the number of channels, not the number of nodes in the network.     

Cognitive Radio Bandwidth Sharing Scheme Based on the Two-way Matching Game

Bandwidth is an extremely valuable and scarce resource, and may become congested to accommodate diverse services in wireless communications. To enhance the efficiency of bandwidth usage, the concept of cognitive radio has emerged as a new design paradigm. In this paper, a new bandwidth sharing algorithm is developed for cognitive radio networks. Under dynamically changing network environments, we formulate the bandwidth sharing problem as a two-way matching game model. In addition, modified game theory is adopted to reach a near Pareto optimal solution while avoiding bandwidth inefficiency. This approach can make the system more responsive to the current network situation. With a simulation study, it is demonstrated that the proposed scheme approximates an optimized solution under widely diverse traffic load intensities.     

A novel grooming algorithm with the adaptive weight and load balancing for dynamic holding-time-aware traffic in optical networks

To maximize the resource utilization of optical networks, the dynamic traffic grooming, which could efficiently multiplex many low-speed services arriving dynamically onto high-capacity optical channels, has been studied extensively and used widely. However, the link weights in the existing research works can be improved since they do not adapt to the network status and load well. By exploiting the information on the holding times of the preexisting and new lightpaths, and the requested bandwidth of a user service, this paper proposes a grooming algorithm using Adaptively Weighted Links for Holding-Time-Aware (HTA) (abbreviated as AWL-HTA) traffic, especially in the setup process of new lightpath(s). Therefore, the proposed algorithm can not only establish a lightpath that uses network resource efficiently, but also achieve load balancing. In this paper, the key issues on the link weight assignment and procedure within the AWL-HTA are addressed in detail. Comprehensive simulation and experimental results show that the proposed algorithm has a much lower blocking ratio and latency than other existing algorithms.     

基于图转换的无线接入点关联优化算法

无线接入点关联是 Wi-Fi 系统中的一个基础问题。已有的研究主要集中在考虑带宽容量约束条件下的各种AP关联问题。这些研究没有从用户的角度考虑带宽需求,从用户的带宽需求出发,以最多带宽分配的AP关联为优化目标,考虑混合型网络架构下的Wi-Fi系统的无线接入点关联优化问题。与已有研究方法不同,通过图转换技术,并将问题转化为流图上的优化问题,提出基于网络流的优化求解算法,并从理论上证明算法的最优性。最后,通过对比实验进一步证明了算法的优越性。