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。     

虚拟网络可生存的启发式可靠映射算法

针对虚拟网络可靠映射问题,引入虚拟网络可生存约束条件,确保在底层网络单节点失效情况下,被映射虚拟网络剩余部分仍保持连通,最大程度确保虚拟网络的完整性和服务的连续性。以最小化底层网络映射开销为目标函数,建立虚拟网络可靠映射的整数线性规划模型,提出一种虚拟网络可生存的启发式可靠映射算法RHM-SVN并进行求解。实验结果表明,该算法能够有效降低资源平均利用率,提高映射成功率、底层网络平均收益和虚拟网络恢复成功率。     

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。     

在SDON中面向成本优化的虚拟光网络映射方法

结合软件定义光网络和光网络资源虚拟化的技术背景,对虚拟光网络成本优化问题进行了深入研究。在软件定义光网络中采用软件定义光网络基础服务架构和网络资源抽象的虚拟光网络服务架构,通过引入虚拟光网络的映射模型,提出了虚拟光网络映射策略和虚拟光网络协同映射规划方法,解决了面向成本优化的虚拟光网络映射方法,可为未来光网络虚拟化技术的应用提供技术支撑。     

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。     

跨域虚拟网络映射问题研究

该文研究网络虚拟化环境下的跨域虚拟网络映射问题,提出一种集中式管理、分布式控制的分层分域虚拟网络资源管理架构。在此基础上,构建了一种有效的虚拟网络跨域映射框架,在此框架下将涉及到跨域的虚拟网络请求进行划分,并以最小化虚拟网络映射开销为目标,基于优化的人工蜂群算法进行最优划分方案的求解。仿真结果表明该方法在平均划分时间、虚拟网络请求接受率和平均额外映射等方面相比传统方法具有更好的性能。     

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。     

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.     

基于节点可靠性感知和共享路径保护的虚拟网映射算法研究

网络虚拟化技术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。对在保证虚拟网络可靠性的同时如何最小化底层网络映射开销问题进行研究,设计了一个新的启发式算法对其进行求解。实验表明,相比其他算法,所提算法网络带宽资源开销更低。     

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.     

基于粒子群优化的虚拟网络映射算法

本文以提高底层网络资源利用效率为目标,在底层网络不需要支持路径分裂的情况下,建立了虚拟网络映射问题的整数线性规划模型,并提出了一种新的基于粒子群优化的虚拟网络映射算法.该算法以映射开销作为适应度函数,重新对粒子的参数和相关操作进行了定义.模拟实验结果表明,与已有研究成果相比,该算法显著地提高了底层网络长期平均运营收益与...     

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.     

Adaptive scheme based on status feedback for virtual network mapping

Network virtualization is considered as a powerful way to deploy different network architectures and protocols over a shared physical infrastructure.Virtual network(VN)embedding plays an important role in the network virtualization environment.Virtual network embedding is mainly about mapping virtual nodes and virtual links onto the physical network resources efficiently.However,load balancing of substrate network has not received much consideration.This paper proposes an adaptive virtual network mapping algorithm based on status feedback.The main contribution is to embed the virtual network requests according to the current load distribution of substrate network.This adaptive algorithm differentiates the residual bandwidth of substrate links and takes full advantage of the multi-path to improve the load balancing of the substrate network.Simulation experiments show that the proposed algorithm improves the load distribution of substrate network distinctly while reducing the average substrate link stress significantly.     

Distributed parallel algorithms for online virtual network embedding applications

Network virtualization (NV) has ubiquitously emerged as an indispensable attribute to enable the success of the forthcoming virtualized networks (eg, 5G network and smart Internet of Things [IoT]). Virtual network embedding (VNE) is the major challenge in NV that allows multiple heterogeneous virtual networks (VNs) to simultaneously coexist on a shared substrate infrastructure. A great number of VNE algorithms have been proposed, but over the past decades, most of them are only targeting for VNE node mapping. In this paper, we propose two distributed parallel genetic algorithms, which are based on two versions of crossover and mutation schemes, for online VN link embedding problems with low latency and high efficiency. Furthermore, we conduct a time analysis on the executing time of independently distributed parallel computing machines in details. This comprehensive analysis validates the parallel computing scalability on an identical number of predefined parallel machines. Extensive simulations have shown that our proposed algorithms can achieve better performance than integer linear programming (ILP)–based solutions while meeting the stringent time requirements for online VN embedding applications. Our proposed algorithms yield superior performance in running time with 32.78% up to 1727.8% faster than existing popular VNE algorithms. Additionally, the theoretical analysis indicates that the execution time can be reduced to logarithmic times by applying proposed distributed parallel algorithms.     

Virtual network embedding in software-defined hybrid networks

Network virtualization provides a powerful way of sharing substrate networks. Efficient allocation of network resources for multiple virtual networks (VNs) has always been a challenging task. In particular, with the demands of the customized VN requests are increasing, many problems arise as network conditions change dynamically. Especially, when the resources conflicting appear during the lifetime of VNs, it needs service provider (SP) to provide a fast and effective solution. Recently, software defined network (SDN) has emerged as a new networking paradigm, SDN’s centralized control and customizable routing features present new opportunities for convenient and flexible embedding VNs in the network. However, due to the limitations of the SDN, in the short term, replacing all legacy devices in current operational networks by SDN-enabled switches is impractical. Thus, in our study, we focus on the scenario of VN embedding (VNE) in software-defined hybrid networks. In this work, first of all, we propose partially deploying SDN nodes, and then, we use the characteristics of SDN to allocate resources for VN requests, and redirect the path for requests conflict in hybrid SDN network. We formulate the problems and provide simple algorithms to solve them. Simulation results show that our scheme is high responsiveness and acceptance ratio.     

等规模虚拟网络映射问题的反向和双向灌水方法

Previous Virtual Network (VN) embedding researches mostly focus on developing heuristic algo-rithms to enhance the efficiency of a physical re-source. However, in the equal-scale condition, where the scale of a VN is similar to that of a substrate net-work, the number of successfully mapped VNs de-creases sharply since bottlenecks form easily in the substrate network and disturb the embedding process. In this paper, reversed and bidirectional irrigation methods are proposed for the equal-scale and all-scale conditions. The two proposed methods can be com-bined with most of the existing heuristic algorithms and map a relatively large number of VNs by reducing the potential substrate bottlenecks. The simulation re-sults show that the reversed irrigation method almost doubles the successfully mapped Revenue than the traditional one in the equal-scale condition. Mean-while, the bidirectional irrigation method achieves the synthetically best performance in almost all scale con-ditions.     

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.     

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.     

VNE-AFS：基于人工鱼群的网络虚拟化映射算法

虚拟网络资源映射是云计算研究领域的一个难点问题。以降低底层网络映射开销为目标,提出一种基于人工鱼群的网络虚拟化映射算法VNE-AFS。根据虚拟网络请求对底层网络节点和链路的约束关系建立二进制组合优化模型,并利用人工鱼群算法实现虚拟网络资源向底层网络资源的近似最优映射。实验结果表明,与现有的虚拟网络映射算法相比,该算法有效地降低了底层网络的开销和求解时间,提高了虚拟网络映射的成功率、平均收益和资源利用率。