链路可靠性感知的差异保护虚拟光网络映射

针对弹性光网络的多链路故障影响虚拟光网络映射性能问题,提出一种链路可靠性感知的差异保护虚拟光网络映射（RA-DPVONE）方法.根据光节点的资源特性与相邻链路故障概率,该方法设计了光节点重要性评估准则和优先映射方法.根据候选光路上的可用频谱资源和链路故障概率,设计虚拟链路映射的工作光路和保护光路的链路代价更新公式,仅为不满足可靠性需求的虚拟链路映射资源共享保护光路.仿真结果表明,所提方法能降低网络的带宽阻塞率,提高虚拟网络请求接受率和弹性光网络的频谱资源利用率.     

基于灾难预测多区域故障的虚拟光网络生存性映射

生存性虚拟光网络映射是提高光网络应对灾难故障的重要技术保障措施。为解决灾难性多区域故障导致弹性光网络的带宽容量损失问题,该文提出基于灾难预测故障模型的蚁群优化虚拟光网络映射 (DFM-ACO-VNM)算法。在该算法中,设计基于光节点资源和相邻链路的全局潜在故障概率的光节点排序映射准则,并设计启发式信息公式实现多区域故障下最小带宽容量损失的虚拟节点和虚拟链路协同映射。仿真结果表明,该文所提算法在多区域故障时能降低带宽容量损失,减少带宽阻塞率和提高频谱利用率。     

虚拟网络映射生存性能提升的方法

虚拟网络映射到实体物理网络,在持续工作过程中,不可能不发生故障。文章分析虚拟网络映射中发生的故障问题,特别是底层物理网络故障的问题。针对物理网络的故障问题,首先提出利用备份资源解决的方法,更进一步提出无备份资源的虚拟网络映射故障的解决方法,并给出对于节点故障和链路故障的具体解决方案,最后兼顾网络利用率和可靠性阐述融合的解决方案,对进一步研究进行展望。     

一种碎片感知的安全虚拟网络重构方法

针对现有的虚拟网络重构算法对物理网络中产生的碎片资源考虑不够周到,导致其对在线虚拟网络映射算法的性能改善不够显著的问题,该文定义了一种网络资源碎片度度量方法,并提出一种碎片感知的安全虚拟网络重构算法。该算法通过周期性考虑物理网络中节点的碎片度,选择出待迁移虚拟节点集合;通过综合考虑物理网络的碎片度减小量和虚拟网络的映射开销减少量,选择出最佳的虚拟节点迁移方案。仿真结果表明,该算法的请求接受率和收益开销比均优于当前的重构算法,特别是在收益开销比方面的优势更加明显。     

节点中介性和频谱离散度感知虚拟光网络生存性协同映射

虚拟网络的映射策略影响弹性光网络(EON)资源可用性和网络生存性。该文提出一种基于节点间距离和频谱离散度感知的虚拟光网络生存性协同映射(CM-DSDA)算法,研究节点计算资源和拓扑位置中介性的光节点排序策略,设计频谱离散度方法评价链路频谱碎片化程度。在虚拟链路的生存性映射中,选择邻接已映射节点中消耗频隙数少且频谱离散度低的工作光路和保护光路协同映射虚拟网络。仿真结果表明所提算法能有效地提高EON的频谱占用率和减少带宽阻塞率。     

信任感知的安全虚拟网络映射算法

针对网络虚拟化技术带来的新的安全威胁,将信任关系和信任度引入到虚拟网络资源分配中,量化分析了网络虚拟化环境中的安全问题,构建了安全虚拟网络映射的数学模型,并在映射过程中考虑节点的局部和全局重要性,采用逼近理想排序法方法对节点进行多属性重要度排序,提出了一种信任感知的安全虚拟网络映射算法。仿真结果表明,该算法在满足虚拟网络请求可信需求的条件下,获得了较好的映射成功率、映射收益和资源利用率。     

一种基于拓扑势的虚拟网络映射算法

该文针对现有的虚拟网络映射算法对网络中节点的拓扑属性考虑不够周到,导致其请求接受率和收益开销比较低的问题,将物理学里的场论思想引入了虚拟网络映射,并提出一种基于拓扑势的虚拟网络映射算法。该算法在节点映射阶段,通过计算节点的拓扑势、节点的资源能力、待映射节点与已映射节点之间的距离,将虚拟节点映射至最佳的物理节点。在链路映射阶段,通过计算物理路径的可用带宽和路径跳数,将虚拟链路映射至最佳的物理路径。仿真实验表明,该算法在多种虚拟网络到达强度下的请求接受率和收益开销比均优于当前的虚拟网络映射算法。     

面向节点异构的能耗感知虚拟网络映射算法

在底层网络节点异构的环境中,能耗优化的虚拟网络映射问题并不是最小化工作节点和链路数。该文针对此问题,构建底层网络节点和链路的负载能耗模型,并以能耗最优为目标,建立虚拟网络映射问题的数学模型,提出一种能耗感知虚拟网络映射算法。该算法在节点映射阶段以最小化能耗和协调链路映射为原则,将虚拟节点映射至综合资源能力最大的底层节点上,并采用改进的能耗感知k最短路径法进行链路映射。仿真结果表明,该算法显著减少虚拟网络映射的能耗,且底层网络节点异构性越大,能耗优势更为明显。     

一种生存性军事虚拟网络映射新方法

针对生存性的军事虚拟网络映射问题,提出了生存性的军事虚拟网络映射需要遵循的原则。构建了虚拟网络映射模型,并采用蝙蝠算法进行求解。针对故障情况,提出了区分服务的故障恢复策略,对于高优先级虚网请求提前构建保护路径,对于低优先级虚网请求则提出基于链路可靠性的故障迁移算法,为了减少带宽消耗适当考虑了节点迁移策略。最后通过仿真验证了算法在虚拟网络运行成功率、故障修复率和链路利用率方面相比其他算法具有更好的性能。     

虚拟网络映射模型和算法研究

虚拟网络映射是网络虚拟化的关键问题之一,其目的是在满足虚拟网络资源需求的前提下,为该虚拟网络分配合适的底层网络节点和链路资源,从而在共享的物理网络基础设施之上构建彼此隔离的多重异构虚拟网络,为网络基础创新研究提供实验环境和平台,为网络新应用提供承载服务。论述了虚拟网络映射模型和映射算法,并提出基于最小割集理论设计VN映射算法。     

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.     

Programmable virtual network instantiation in IaaS cloud based on SDN

A possible approach to cope with the diversity of future networks is to set up multiple isolated virtual networks on top of a single shared physical substrate, and each virtual network is customized to some specific purposes. However, in the current realization of virtualized infrastructure, the OpenStack infrastructure as a service (IaaS) cloud, whose isolation and programmability are limited in terms of scalability and performance. To overcome these limitations, we propose a solution based on software defined networking (SDN) which is composed of a centralized server and distributed agents. The server has complete view of the whole network substrate, and is responsible for the installation and management of virtual network through the distributed agents. Each agent has the local view of the substrate node. They can manage the local resources, dispatch and filter the inner- programmable virtual network (PVN) traffic based on MAC isolation which is more scalable than virtual local area network (VLAN) and more efficient than GRE. Our prototype implementation shows that this architecture is feasible and provides a better compromise between flexibility and performance than the solo centralized and distributed solutions.     

A hybrid virtual network mapping algorithm based on threshold load

The virtual resource management architecture for satellite networks currently suffers from a very poor virtual network mapping success rate. This arises because of the need to map multiple heterogeneous virtual networks to the underlying satellite network. Most heuristic algorithms divide virtual network mapping into node mapping and link mapping, which aims to reduce the complexity of the problem. However, this approach is not well suited to highly dynamic satellite networks. In this paper, we propose a hybrid virtual network mapping algorithm that is based on threshold load. This takes the overall load for the nodes as its optimization objective, and combines the idea of backtracking contained in 1‐stage mapping methods and the idea of global optimization contained in 2‐stage mapping methods. The algorithm reduces the complexity of backtracking computation, while avoiding any incompleteness that might result from separating nodes and link mapping. The success rate for virtual network mapping is thus improved, as is the utilization rate for satellite network resources.     

基于链路可靠性的无线虚拟网络分配方法

针对无线网络链路可靠性差影响无线虚拟网络的分配这一问题,提出了一种基于链路可靠性的无线虚拟网络分配算法（WVNEA-LR）。该算法通过物理网络拓扑预处理和允许同一个虚拟请求中的多个虚拟节点映射到同一个物理节点上的方法,提高了Vn构建成功率和节约了物理链路资源。利用Q因子改善了因拓扑分配稀疏时Vn构建成功率低的问题。此外,WVNEA-LR的节点分配为链路分配作了准备,并通过选择可靠性高的承载路径保证了分配后的Vn具有高可靠性。仿真结果表明, WVNEA-LR获得较好的虚拟网络构建成功率、较高的收益成本比和资源利用率。     

集中与分布:协同虚拟网络映射

结合传统集中式和分布式两类算法各自的特性,提出了协同虚拟网络映射算法。该算法保留了集中式算法中拥有全局视野的中心控制实体,负责总体控制和关键决策,同时将具体映射方案的计算过程交给有限的底层网络子集实现;唯一的中心控制实体与多个底层节点相互配合协作,共同完成虚拟网络映射的整个过程。该算法继承了集中式和分布式算法各自的优势,有效弥补了二者的缺陷,初步的仿真试验也证明了其可行性和有效性。     

A model for virtual network embedding using Artificial Bee Colony

In a network virtualization environment, a significant research problem is that of virtual network embedding. As the network virtualization system is distributed in nature, an effective solution on how to optimally embed a dynamically generated virtual network request on the substrate networks that are owned and managed by multiple infrastructure providers needs proper attention. The problem is computationally hard, and therefore, many approaches, implying heuristics/meta‐heuristics, have been applied for the same. A meta‐heuristic, Artificial Bee Colony algorithm is getting popular due to its robustness toward complex problem solving. A novel approach based on Artificial Bee Colony to address the dynamic virtual network embedding problem in a multiple infrastructure provider scenario is proposed in this work. Bee population is initialized by using a greedy heuristic in which the number of substrate networks together with virtual network requests constructs a bee. Generated solution, in the population, is improvised by using greedy selection that explores a local search method adopted by the bees. In greedy selection, the new candidate source is memorized by the bee if its fitness is better than the fitness of the existing source. The performance study of the proposed model is done by simulation over various metrics such as embedding cost, embedding time, and acceptance ratio. A comparative study is conducted with other nature‐inspired virtual network embedding algorithms on these metrics. The findings affirm that the proposed virtual network embedding approach performs well and produces better results.     

分布式环境中基于协商的虚拟网映射算法

网络虚拟化技术可以在共享的底层物理网络上为用户同时提供多种可定制的服务网络。目前的虚拟网映射算法比较依赖于集中式的管理节点,使其在可靠性和适用范围等方面存在诸多问题。为此,提出了一种分布式环境下的虚拟网映射算法,该算法通过多个节点之间的相互协商来完成虚拟网的映射,并且在降低通信开销和缩短虚拟链路的路径长度方面进行了相应改进。实验结果表明,该算法与同类型算法相比,在资源利用率和通信开销方面具有一定的优越性。     

可靠的虚拟网络映射算法研究

网络虚拟化技术允许多个异构的虚拟网络共享一个底层物理网络资源,为目前的网络架构提供了一种有效的扩展手段.近年来,底层网络基础设施失效事件频发,因此如何提高虚拟网络的可靠性成为目前该领域一个研究热点.本文针对底层节点失效后虚拟拓扑如何最大化连通问题进行研究,设计了一种基于割集和拥塞感知的虚拟网络映射机制.实验表明,该方法在不预留保护资源的情况下,可获得更好的底层网络长期运行平均收益.     

虚拟网络映射高效节能运输模型及算法

网络虚拟化使得智能能量感知网络部署成为可能,已有研究忽略了节点映射能耗最优化。本文把节点映射能耗优化问题转化为生产地与销售地之间物资运输代价最优化问题,建立高效节能节点映射运输模型。根据最大元素法,提出了混合一阶段与两阶段映射算法,在链路映射的约束下找到节点分配最小能耗代价最优解;利用主动休眠策略,提出了基于运输模型的主动休眠虚拟网络映射节能算法;利用节点可重复映射技术,提出了基于运输模型的节点可重复映射算法,进一步提高了底层网络资源休眠数量。仿真结果验证了本文所提算法能够显著降低系统能耗,适合大规模高效节能虚拟网络映射。     

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.