软件定义网络中基于效率区间的负载均衡在线优化算法

在大型复杂软件定义网络中,为提高网络负载均衡,减少控制器与交换机间的传播时延,该文提出一种基于效率区间的负载均衡在线优化算法。在初始静态网络中,通过贪心算法选择初始控制器集合,并以其为根节点构建M棵改进代价的最小生成树(MST),确定初始M个负载均衡的子网;当网络流量发生变化时,通过广度优先搜索(BFS)调整子网间交换机映射关系使其满足效率区间,保证任意时刻网络的负载均衡。算法均以网络连通性为基础,且均以传播时延为目标重新更新控制器集合。仿真实验表明,该算法在保证任意时刻网络负载均衡的同时,可以保证较低的传播时延,与Pareto模拟退火算法、改进的K-Means算法等相比,可以使网络负载均衡情况平均提高40.65%。     

一种软件定义无线网络负载均衡架构及算法

软件定义网络( SDN)为实现异构无线网络中的负载均衡提供了新的思路。设计了一种软件定义的无线网络负载均衡架构,并提出对应算法。首先,根据接收信号强度构建候选网络列表;其次,根据各候选网络的可用负载比率标准差进行负载差异分级;再次,将服务质量匹配度函数和负载均衡指数线性组合成联合优化函数,并根据负载差异分级对联合优化的权重进行动态调整,合理设置门限进行接纳控制。与传统算法相比,所提算法一方面可使各类业务阻塞率明显降低大约20%,另一方面使不同网络的归一化负载更加接近。该算法在进行网络负载均衡的同时,能够有效降低业务阻塞率,从而有效提升异构无线网络的整体性能。     

基于成本及功耗联合优化的SDN虚拟网络映射算法

针对多个虚拟网络请求(Virtual Network Request,VNR)动态到达的网络场景,本文提出一种基于成本及功耗联合优化的软件定义网络(Software-Defined Networking,SDN)虚拟网络映射(Virtual Network Embedding,VNE)算法.在对虚拟节点及链路映射成本及功耗进行评估的基础上,建模VNE成本及功耗的代价函数,进而在满足资源需求等约束条件下,建模基于代价函数最小化的VNE模型.该优化问题为整数线性规划问题,难以直接求解;为解决此问题,提出基于时间窗的虚拟网络批处理映射策略动态处理在线请求.继而针对特定时间窗内的VNR,将其转换为虚拟节点映射子问题和虚拟链路映射子问题,并应用启发式算法对两个子问题分别进行求解,从而确定VNR映射策略.仿真结果表明,所提算法能显著减少VNE成本及功耗,提高VNR接受率.     

应用粒子群优化的绿色虚拟网络映射算法

绿色网络是近年来网络技术研究的热点,以节能为优化目标的虚拟网络映射算法成为基于网络虚拟化技术中资源分配研究的重点.提出了应用粒子群优化的绿色虚拟网络映射算法,重定义粒子群优化算法中的参数和粒子进化行为,以关闭底层网络节点和链路数量最多为适应度函数,在较低的算法复杂度条件下,获得绿色虚拟网络映射的最优解.仿真结果表明,与对比算法相比,静态环境下所提算法的运行时间大幅度降低;动态环境下所提算法的节点关闭率、链路关闭率、虚拟网络请求接受率均有所提升,算法运行时间也大大缩短.     

基于成本及功耗联合优化的SDN虚拟网络映射算法

针对多个虚拟网络请求(Virtual Network Request,VNR)动态到达的网络场景,本文提出一种基于成本及功耗联合优化的软件定义网络(Software-Defined Networking,SDN)虚拟网络映射(Virtual Network Embedding,VNE)算法.在对虚拟节点及链路映射成本及功耗进行评估的基础上,建模VNE成本及功耗的代价函数,进而在满足资源需求等约束条件下,建模基于代价函数最小化的VNE模型.该优化问题为整数线性规划问题,难以直接求解;为解决此问题,提出基于时间窗的虚拟网络批处理映射策略动态处理在线请求.继而针对特定时间窗内的VNR,将其转换为虚拟节点映射子问题和虚拟链路映射子问题,并应用启发式算法对两个子问题分别进行求解,从而确定VNR映射策略.仿真结果表明,所提算法能显著减少VNE成本及功耗,提高VNR接受率.     

软件定义网络中基于Q-学习的负载均衡算法

针对软件定义网络(Software Defined Network,SDN)的负载均衡问题,为使网络的资源分配更加合理,防止网络拥塞,设计了一种基于Q-学习的负载均衡(Q-learning Load Balance,QLLB)算法,可根据网络环境自行作出决策,避免网络拥塞,实现网络资源的合理分配.与最短路径算法Dijkstra、蚁群算法进行的性能对比结果表明,QLLB算法有效实现了负载均衡,使得各个链路的带宽利用率更加平均,吞吐量分别提升了约8％和2％,可有效提升网络性能.     

网络虚拟化中动态资源分配算法研究

针对网络虚拟化中资源分配问题,提出一种动态的资源分配算法。算法根据物理节点平均负载差异度,结合当前物理网络容忍的节点负载差异动态地进行虚拟节点迁移,并通过综合影响因子为虚拟节点选择合适的目标宿主,减少虚拟节点迁移对物理链路带宽和虚拟链路时延的影响。仿真实验表明,该算法能使物理节点上的负载分布均衡,同时对时延和带宽的影响较小。     

联合能耗与负载均衡的虚拟网络映射方法

为解决弹性光网络中虚拟网络映射时能耗严重、资源分配不均的问题,该文提出一种联合能耗与负载均衡的虚拟网络映射（PC-LB-VONE）方法.在虚拟节点映射时,选择相邻链路长度短、光节点计算资源多与相邻链路带宽资源多的光节点映射.在虚拟链路映射时,提出一种基于极大团的候选光路资源匹配度单路径映射策略.当单路径映射失败时,设计基于链路负载均值的多路径映射策略.仿真结果表明,所提方法能在减少弹性光网络能耗的同时均衡网络负载.     

软件定义网络中面向时延和负载的多控制器放置策略

在多控制器管理的软件定义网络(SDN)中,时延和负载是控制器放置问题(CPP)要考虑的重要因素。该文以降低控制器之间的传播时延、流请求的传播时延和排队时延、均衡控制器间负载为目标,提出一种控制器放置及动态调整的策略,其中包括用于初始控制器放置的负载均衡算法(BCRA)和遗传算法(GA),用于动态调整控制器负载的在线调整算法(ADOA)。以上算法均考虑网络连通性。仿真结果表明:在初始控制器放置时,在保证流请求的传播时延、排队时延和控制器传播时延较低的情况下,BCRA部署在中小型网络中时,其负载均衡性能与GA相近且优于k-center和k-means算法;GA部署在大型网络中时,与BCRA, k-center和k-means算法相比,使得负载均衡率平均提高了49.7%。在动态情况下,与现有动态调整算法相比,ADOA可以保证较低排队时延和运行时间的同时,仍能使负载均衡参数小于1.54。     

流特征感知的软件定义网络控制器动态关联机制

在部署分布式控制平面的软件定义网络中,控制器与交换机的关联仅以数据流请求的数量分布作为控制资源分配的依据。该文针对这一问题,以数据流的源目的地址特征为例,对不同特征数据流的控制资源消耗进行了分析,提出在控制资源分配中应对数据流的特征分布加以考虑。然后,设计了一种流特征感知的控制器关联决策机制,并针对网络流的动态变化特性设计了一种快速求解算法。仿真结果表明,与基于负载均衡的机制对比,所提机制在使用模拟退火算法求解时能节省10%～20%的控制资源消耗;所提快速求解算法可节省10%的资源消耗,且相比模拟退火算法具有较大的速度优势和良好的可扩展性。     

Dynamic recovery for survivable virtual network embedding

Network virtualization is a promising way to overcome the current ossification of the Intemet. It is essential challenge to find effective, efficient and robust embedding algorithms for recovering virtual network. The virtual network mapping algorithm based on integer programming which was proposed months ago. But it did consider the faults of physical network resources, which is so called survivable virtual network embedding （VNE） problem. Previous strategies for enabling survivability in network virtualization focused on providing protection for the physical network or enhancing the virtual networks by providing backup physical resources in advance, and treated all the physical failures as link failures. In the article, a dynamic recovery method is proposed to solve the survivable virtual network embedding problem based on the integer programming VNE algorithm. The dynamic recovery method doesn＇t need to backup physical resources and it makes more substrate resources which can be used in the embedding. The dynamic recovery process will be activated only when physical failures occur. Different algorithms are used to recovery node and link failures. Simulations show that the method helps to recover almost all of physical failures by finding the substitute nodes and paths, and its performance is very close to that of pure VNE method without considering physical failures.     

A unified enhanced particle swarm optimization‐based virtual network embedding algorithm

Virtual network (VN) embedding is a major challenge in network virtualization. In this paper, we aim to increase the acceptance ratio of VNs and the revenue of infrastructure providers by optimizing VN embedding costs. We first establish two models for VN embedding: an integer linear programming model for a substrate network that does not support path splitting and a mixed integer programming model when path splitting is supported. Then we propose a unified enhanced particle swarm optimization‐based VN embedding algorithm, called VNE‐UEPSO, to solve these two models irrespective of the support for path splitting. In VNE‐UEPSO, the parameters and operations of the particles are well redefined according to the VN embedding context. To reduce the time complexity of the link mapping stage, we use shortest path algorithm for link mapping when path splitting is unsupported and propose greedy k‐shortest paths algorithm for the other case. Furthermore, a large to large and small to small preferred node mapping strategy is proposed to achieve better convergence and load balance of the substrate network. The simulation results show that our algorithm significantly outperforms previous approaches in terms of the VN acceptance ratio and long‐term average revenue. Copyright © 2012 John Wiley & Sons, Ltd.     

Embedding and reconfiguration algorithms for service aggregation in network virtualization

Network virtualization and transmission quality optimization are promising techniques for future Internet. Previous researches on virtual network embedding focused on efficient utilization of network resources. In this paper, we present a virtual network embedding scheme that aims at improving the effect of transmission quality optimization. In order to enable more service benefit from optimization, the embedding algorithm presented in this paper follows the service aggregation embedding principle. We also develop a reconfiguration algorithm based on service aggregation and load balance. Simulation experiments demonstrate that the proposed algorithms can achieve good performance on service aggregation as well as efficient resource utilization. Copyright © 2014 John Wiley & Sons, Ltd.     

QoS‐aware cross‐domain collaborative energy‐saving mechanism for FiWi virtual networks

The fiber‐wireless (FiWi) access network is a very promising solution for next‐generation access networks. Because of the different protocols between its subnets, it is hard to globally optimize the operation of FiWi networks. Network virtualization technology is applied to FiWi networks to realize the coexistence of heterogeneous networks and centralized control of network resource. The existing virtual resource management methods always be designed to optimize virtual network (VN) request acceptance rate and survivability, but seldom consider energy consumption and varied requirements of quality of service (QoS) satisfaction, which is a hot and important topic in the industrial field. Therefore, this paper focuses on the QoS‐aware cross‐domain collaborative energy saving mechanism for FiWi virtual networks. First, the virtual network embedding (VNE) model, energy consumption model, and VNE profit model of FiWi networks are established. Then, a QoS‐aware in‐region VN embedding mechanism is proposed to guarantee service quality of different services. After that, an underlying resource updating mechanism based on energy efficiency awareness is designed to realize low‐load ONU and wireless routers co‐sleep in FiWi networks. Finally, a QoS‐aware re‐embedding mechanism is presented to allocate proper resource to the VNs affected by the sleeping mechanism. Especially for video VNs, a re‐embedding scheme which adopts traffic splitting and multipath route is introduced to meet resource limitation and low latency. Simulation results show that the proposed mechanism can reduce FiWi network's energy consumption, improve VNE profit, and ensure high embedding accepting rate and strict delay demand of high‐priority VNs.     

基于资源区域聚集度的虚拟网映射算法

虚拟网映射是网络虚拟化研究中亟待解决的问题,针对已有映射算法中存在的对于网络拓扑信息利用不足的现状,该文提出了基于资源区域聚集度的虚拟网映射算法(RCI-VNE)。在映射预处理阶段,根据局部拓扑信息和区域资源聚集度提出节点区域资源聚集评价算法。在节点映射阶段,提出一种基于节点区域资源聚集排名的2-近邻聚集映射算法,该算法将虚拟网节点集中映射到底层网络中可用资源丰富的区域,减小承载链路的长度。实验结果表明,该算法降低了虚拟网映射开销,且具有较高的虚拟网请求接受率和较低的平均执行时间。     

Resource optimization algorithm of combination of NFV and SDN for application of multiple services

Various services of internet of things (IoT) require flexible network deployment to guarantee different quality of service (QoS).Aiming at the problem of IoT service function chain deployment,network function virtualization (NFV) and software defined networking (SDN) were combined to optimize resources.Considering forwarding cost and traffic load balance,a joint optimization model of virtual network function placement and service function chain routing was given and was proved to be NP-Hard.In order to solve this model,two heuristic algorithms were proposed.One was the service chain deployment algorithm of first routing then placing (FRTP) and the other was the placing followed by routing (PFBR) based on node priority.Simulation results demonstrate that FRTP and PFBR algorithm can significantly balance network traffic load while alleviating congestion and improving the acceptance ratio of the chain requests compared with other algorithms.     

Virtual channel load-balanced routing algorithm for Torus networks

In order to improve the network performance furthermore,a routing algorithm for 2D-Torus is investigated from the standpoint of load balance for virtual channels.The 2D-Torus network is divided into two virtual networks and each physical channel is split into three virtual channels.A novel virtual channel allocation policy and a routing algorithm are proposed,in which traffic load is distributed to those three virtual channels in a more load-balanced manner by introducing a random parameter.Simulations of the proposed algorithm are developed with a SystemC-based test bench.The results show that compared with the negative first for Torus networks(NF-T) algorithm,the proposed algorithm can achieve better performance in terms of network latency and throughput under different traffic patterns.It also shows that a routing algorithm with load balance for virtual channels can significantly improve the network performance furthermore.     

弹性光传输基础设施上动态透明虚拟网络嵌入

提出了一个新的动态透明的虚拟网络嵌入（VNE）算法。该算法基于弹性光传输基础设施,同时考虑节点映射和链路映射,用于光正交频分复用（O-0FDM）的网络虚拟化。对每一个虚拟光网络（VON）的请求,该算法首先根据各光纤链路的频谱使用将底层光网络转化成一个分层辅助图,然后在该辅助图的单层上应用一个考虑了所有底层节点的本地信息的节点映射完成链接映射。仿真结果表明,该算法考虑了O-OFDM网络的独特性,并且由于算法提供较低的VON阻塞概率,优于直接应用VNE的参考算法。实际拓扑结构的仿真结果也表明,嵌入的底层路径的平均距离很好地被控制在O-OFDM信号的典型传输范围内。     

云环境下基于迁移的虚拟机集群优化算法

针对云环境中虚拟机集群负载不均衡问题,提出一种基于虚拟机迁移的集群优化算法。通过对节点负载的实时监测,动态调整各种资源的权重,根据资源权重选择可最大程度降低主机负载的虚拟机进行迁移。该算法利用预测机制,消除主机资源利用率的临时越界引起的不必要的虚拟机迁移。在选择目标节点时,采用多目标决策法,兼顾多资源匹配率,服务级目标违背率(SLA)等多种管理目标。实验结果表明,与同类型的负载均衡算法相比,该算法能减少迁移次数,降低SLA违背率。