无线Mesh网络中路由与信道联合分配研究

无线Mesh网络中路由器使用多射频接口并配备多信道传输能有效增加网络吞吐量及降低干扰。研究路由与信道分配问题的目的就是增加网络容量、减少延迟等。文中针对无线Mesh网络中多接口多信道的路由与信道分配问题做了统一考虑,根据路由约束、信道约束、干扰约束以及宽带约束建立了混合整数线性规划（MILP）模型,并提出了基于迭代搜索的启发式算法很好地解决了此问题。仿真结果表明该算法可以提高网络吞吐量,降低延迟。     

基于软件定义网络的多约束QoS双路径路由优化方法

针对当前SDN架构存在路由算法复杂度高、QoS流满意度低和单链路故障等问题,提出了一种基于软件定义网络的多约束QoS双路径路由优化算法(SDN＿MCQDP)。利用控制器获得全局网络状态信息,生成基于目的节点的有向无环图。在多约束QoS路由选择阶段,通过拉格朗日松弛对偶算法将多约束问题转化为线性规划问题。使用反向链路删减得到满足多约束QoS的节点不相交的双路径冗余链路,使链路故障后的数据传输得到保障。从路由计算时间、链路利用率、QoS流满意度等方面对算法进行仿真实验。结果表明,与MODLARAC、QT、RMCDP＿RD、H＿MCOP算法比较,SDN＿MCQDP能够有效降低传输时延,减少路由计算时间,提高链路利用率,且在链路发生故障后仍能满足QoS需求。     

云基础设施中TPL2-SW网络模型的优化

为解决传统树型网络拓扑对大规模云集群造成的性能瓶颈,针对一种新的网络模型TPL 2-SW进行优化,提出了多路径负载均衡路由策略(MCLBR)和转发路由的硬件加速方案。通过在节点间建立网状链路,将负载指数纳入路由判定因素,并允许节点间负载分流;同时基于FPGA实现硬件转发路由器,并验证了在二层语义对多跳传输加速的可行性。仿真实验证明,优化方案可以在TPL 2-SW基础上显著提高网络的吞吐量和传输效率。     

基于蚁群算法的SDN数据中心网络大象流调度研究

针对传统方法调度大象流时容易造成数据中心网络拥塞和负载不均衡等问题,提出一种基于蚁群算法的SDN（software defined network）数据中心网络流量调度算法ACO-SDN。对大象流调度问题建立整型线性规划ILP（integral linear programing）模型,优化目标为最小化最大链路利用率。通过重定义蚁群算法的参数和操作求解ILP模型,得到大象流重路由的最优路径。实验结果表明,与ECMP（equal-cost multi-path routing）和GFF（global first fit）流量调度算法相比,ACO-SDN算法降低了网络最大链路利用率,有效地提高了网络对分带宽。     

基于网格拓扑的无线传感器网络低能耗路由策略

针对无线传感器网络的能量消耗,提出了一种新型高效的低能耗路由算法。基于网格拓扑结构,主要解决了延迟约束下的中继节点选择问题。通过将问题转化为0～1整数线性规划,可以得到最终的中继选择。所研究的算法主要应用于实时无线传感器网络系统,它能够在满足延迟约束的条件下给出低能耗的路由策略。仿真结果表明:提出的算法能有效地减少无线传感器网络的能量消耗,延长网络寿命。     

无线Mesh网络中的多约束QoS路由算法

无线Mesh网络中多媒体数据的实时传输应用日益广泛,这些应用对网络的带宽、时延和抖动有着较高要求,需要无线Mesh网络提供一定的QoS保障机制.QoS路由是实现QoS保障的关键环节.在路由协议AODV的基础上,提出了一种具有多个QoS参数约束的路由算法(MQ-AODV),通过改进路由选择函数及扩展路由维护机制,为多媒体传输应用业务提供QoS保障.在路由发现的过程中,MQ-AODV引入了一个归一化的路由选择函数,简化了多约束路由算法中的NP-complete问题.在路由维护方面,提出了一种路由预先修复机制,在数据流传输过程中保障路径质量.仿真结果表明,MQ-AODV算法比AODV更好地减少了数据流传输的延迟和丢包,有效提高了网络的吞吐量.     

基于Markov模型的WSN汇聚树路由协议

根据工业监控无线传感器网络(WSN)的可靠性和实时性需求,采用跨层优化方法,提出一种基于介质访问控制层Markov模型的汇聚树协议MM-CTP。利用IEEE 802.15.4 WSN链路层动力学Markov模型对单簇网络进行数据帧传输性能分析,改进汇聚树协议的链路质量评估方法,通过计算最优路由梯度,建立网络拓扑,在保证较高数据到达率的同时,使网络延迟最小,以满足工业监控网络的数据传输需求。     

一种多向链路感知的车载Ad Hoc网络传播协议

为了提高车辆自组织网络（Vehicular Ad Hoc Network,VANET）的数据传输效率,并使车辆间的数据通信能够持续进行,提出一种多向链路感知的车载Ad Hoc网络传播协议。为了保证车辆节点在执行通信任务的过程中实现数据的持续传输,防止通信链路频繁断连影响传输质量,提出了车辆网络的时间关联模型来讨论车辆间的速度差与通信持续时间的关系。为了缩短VANET中用于数据传输任务的总时间,协议基于改进蚁群的方法进行了多向链路感知,从而寻找在保证通信需求时间下的最短传输路径。实验结果分析表明,相比基于改进地理信息路由和基于优化链路状态路由的VANET数据传输算法,该算法的数据传输任务完工时间分别缩短了38.4%和27.3%,平均传输延迟分别降低了25.5%和12.1%。     

一种软件定义车载自组织网络的QoS路由算法

车载自组织网络（VANET）是由移动车辆节点组成的移动自组织网络（MANET）,其不依赖基础设施即可建立通信链路实现通信。由于车辆的高机动性和无线通信资源的限制,VANET难以保障车辆业务的服务质量（QoS）。针对该问题,引入软件定义网络（SDN）,提出一种适用于软件定义车载自组织网络（SDN-VANET）的多约束QoS路由算法。利用SDN控制转发分离的优势保障各业务的QoS,SDN控制器会根据车辆业务的截止日期对业务实现顺序调度,并基于蛙跳算法设计自适应中继节点选择算法(AH-SFLA),SDN控制器根据QoS指标和全局拓扑信息计算数据在传输链路上的适度值,以此为基准搜索优化路径。在此基础上设置备选链路机制和QoS资源消耗阈值共同实现路由维护,减少网络故障发生的概率。联合Mininet-wifi和SUMO搭建SDN-VANET环境,并将AH-SFLA路由算法与IGA、IICSFLA进行对比验证分析。实验结果表明,与IGA和IICSFL相比,AH-SFLA在平均端到端延迟指标上分别提高了57.74%和46.6%,丢包率平均降低了29.9%和18.6%,标准化路由开销提升了36.93%和...     

一种基于蚁群算法的容迟网络路由策略

延迟容忍网络(容迟网络)涵盖了星际网络、移动Ad Hoc网络以及偏远地区网络等许多除因特网以外的通信网络.网络的频繁断裂和间歇连接使容迟网络路由问题成为最具挑战的问题之一.蚁群优化算法作为一种在图中寻找优化路径的机率型技术,已广泛应用于许多领域,它具有正反馈、分布式计算和智能型优化等特点.为提高路由算法对网络拓扑变化的适应能力,研究基于蚁群算法的路由策略,并通过其智能自适应优化减少容迟网络传输延迟.首先模型化容迟网络的数据传输问题;其次设计基于蚁群算法的路由策略(ant-colony-based routing,ACR),包括转发和复制两种数据分配方式;最终基于容迟网络公共数据集Infocom Trace和RollerNet Trace进行仿真验证,并与MED,SimBet,Spray和Wait以及EBR等经典算法比较.仿真结果表明:基于转发方式的ACR算法比其他同类型算法至少缩短25.8%的传输延迟,基于复制方式的ACR算法至少降低22.5%的传输延迟.     

Investigation on static routing and resource assignment of elastic all-optical switched intra-datacenter networks基于弹性全光交换技术的数据中心内网的静态路由和资源分配(RSIA)

In this paper, we explore the issue of static routing and spectrum/IT resource assignment (RSIA) of elastic all-optical switched intra-datacenter networks (intra-DCNs) by proposing anycast- and manycast-based integer linear programming (ILP) models. The objective is to jointly optimize the DCN resources, i.e., network transmission bandwidth and IT resources, under different situations. First, for given service-request matrices with unknown network transmission bandwidth and IT resources, we propose anycast and manycast ILP models to minimize the maximum numbers of required network and IT resources to accommodate all the service requests. For anycast RSIA issue, we proposed two different ILP models that are based on node-arc and link-path methods, respectively. Node-arc based manycast ILP model is also proposed for the first time to our knowledge. Second, for given network transmission bandwidth and IT resources and known service-request matrices, we propose node-arc based anycast ILP models to maximize the total number of successfully served service requests. To evaluate the efficiency of anycast and manycast models, all proposed ILP models are evaluated and compared with unicast ILP models. Simulation results show that anycast and manycast ILP models perform much better in efficiently using DCN resources and successfully accommodating more service requests when compared to unicast ILP models under the same network conditions.     

多源多播服务功能链优化部署算法

在软件定义网络和网络功能虚拟化环境下,针对多播中的服务功能链（SFC）部署,探究了多源多播中的联合虚拟网络功能（VNF）部署和流量路由问题,目的是最小化节点资源消耗和链路资源消耗总成本。同时考虑到节点、链路及带宽延迟限制,建立了整数线性规划模型,并提出一种名为多源多播树优化的启发式算法。该算法旨在为所有用户找到最近的源节点,获得多个源、目节点组,为每个组构造一棵多播服务功能树,然后优化多播服务功能树。实验仿真结果表明,与其他启发式算法相比,该算法有效地降低了总成本、链路利用率及时延。     

一种基于多条件约束的QoS路由选择优化算法

基于多条件约束的QoS路由选择优化是当前通信网络中的一个重要问题。研究了一类通信网络的源－目的QoS路由选择问题。通过分析,为了不失一般性,选择时延和丢失率为QoS参数,建立了一个带有丢失率约束－条件的最小时延的QoS路由选择的非线性整数规划模型,并根据模型特点,给出了用线性整数规划迭代求精确解的算法。该算法可以方便地推广到多个QoS参数的情况。最后,实例表明所提出的模型和算法是有效的。     

一种时延约束下可靠性保证的服务功能链部署方法

针对网络功能虚拟化环境中底层网络物理节点随机失效导致网络服务中断问题,提出了一种兼顾网络服务可靠性和时延约束的服务功能链部署方法以保证网络服务的可靠性。首先提出一种相邻虚拟网络功能备份实例资源共享的备份机制和单路径与多路径混合的路由策略,然后对时延约束下服务功能链可靠性部署问题建立混合整数线性规划模型,并设计了基于K最短路径扩展的服务功能链部署算法。仿真结果表明,与现有方法相比,该方法降低了节点和带宽资源开销,并提高了网络服务请求接受率。     

基于骨干网的数据中心网络服务规划设计

数据中心是云计算的核心,而当前基于电交换器、传统多级交换网络、集中放置与管理的数据中心架构无法满足未来云服务对高性能数据中心在可生存性、高可用性与设计灵活性等方面的要求。以网络可生存性和最小化网络代价为目标,针对数据中心的放置、服务路由及保护进行联合优化设计。首先通过设计ILP获取最优解。该ILP集成了p-cycle、服务量备份以及快速重路由等思想,分别针对单个链路或单个服务器损坏进行快速保护。然后进一步给出一种启发式算法,该算法包含数据中心的放置及服务路由和快速保护两大步骤。ILP和启发式两种方法最终都通过广泛的仿真实验进行了验证。     

A virtual service placement approach based on improved quantum genetic algorithm

Despite the critical role that middleboxes play in introducing new network functionality, management and innovation of them are still severe challenges for network operators, since traditional middleboxes based on hardware lack service flexibility and scalability. Recently, though new networking technologies, such as network function virtualization (NFV) and software-defined networking (SDN), are considered as very promising drivers to design cost-efficient middlebox service architectures, how to guarantee transmission efficiency has drawn little attention under the condition of adding virtual service process for traffic. Therefore, we focus on the service deployment problem to reduce the transport delay in the network with a combination of NFV and SDN. First, a framework is designed for service placement decision, and an integer linear programming model is proposed to resolve the service placement and minimize the network transport delay. Then a heuristic solution is designed based on the improved quantum genetic algorithm. Experimental results show that our proposed method can calculate automatically the optimal placement schemes. Our scheme can achieve lower overall transport delay for a network compared with other schemes and reduce 30% of the average traffic transport delay compared with the random placement scheme.     

Fine two-phase routing over shortest paths with traffic matrix

This paper presents an IP finely-distributed load-balanced routing scheme based on two-phase routing over shortest paths, where the traffic matrix is given. It is called the fine two-phase routing (F-TPR) scheme. F-TPR more finely distributes traffic from a source node to intermediate nodes than the original TPR. F-TPR determines the distribution ratios to intermediate nodes for each source–destination node pair independently. To determine an optimum set of distribution ratios, a linear programming (LP) formulation is derived. We compare the F-TPR scheme against the TPR scheme and the sophisticated traffic engineering (TE) scheme of Multi-Protocol Label Switching (MPLS-TE). Numerical results show that F-TPR greatly reduces the network congestion ratio compared to TPR. In addition, F-TPR provides almost the same network congestion ratios as MPLS-TE, the difference is surprisingly less than 0.1% for the various network topologies examined. In addition, considering the practical implementation of F-TPR for routers, we also investigate the case that traffic from a source node to a destination node is not allowed to be split over multiple routes. The non-split problem is formulated as an integer linear programming (ILP) problem. As it is difficult to solve the ILP problem within practical time, two heuristic algorithms are presented: Largest Traffic Demand First (LTDF) and a Random Selection (RS). The applicability of LTDF and RS are presented in terms of network size. We find that non-split F-TPR also matches the routing performance of MPLS-TE within an error of 1%, when network size is large enough.     

OPTIMIZATION OF SPARE CAPACITY IN WDM NETWORKS FOR REAL-TIME SERVICE RESTORATION

In the case of network malfunction a network with restoration capability requires spare capacity to be used. Optimization of the spare capacity in this case is to find the minimum amount of spare capacity for the network to survive from network component failures. In this paper, the optimization of the spare capacity problem is investigated for the wavelength division multiplexing (WDM) mesh networks without wavelength conversion. To minimize the spare capacity, we will optimize both the routing and the wavelength assignment. This combinatorial problem is usually called the routing and wavelength assignment (RWA) problem and it is well known to be NP-hard. We give an integer linear programming (ILP) formulation for the problem. Due to the excessive run-times of the ILP, we propose a hybrid genetic algorithm approach (GA) for the problem. For benchmarking purpose, simulated annealing (SA) and Tabu search (TS) are also applied to this problem. To validate the effectiveness of the proposed method, the approach is applied to the China network, which has a more complicated network topology. Simulation results are very favorable to the GA approach.