一种MPLS网络拥塞最小化的全局路由优化算法

提出一种启发式群搜索双螺旋优化算法,求解MPLS网络路由全局优化问题,优化目标是使 网络拥塞最小化。算法采用群局部搜索,利用混沌变量产生一组分布好的初始解,在邻域搜索过程中融入启 发式信息,并设计了特别的贪婪重路由以及扩展贪婪原则,提高了算法效率和全局搜索能力。通过仿真比较 说明了所提算法的有效性,及其显著改善网络性能的意义。     

最小化路径代价和流量均衡模型及算法

流量均衡是流量工程中为避免网络拥塞经常采用的路由优化目标,如何选择路径以使流量达到均衡分布是流量路由的研究热点和难点.为了最小化网络拥塞,该文在指出网络拥塞决定于流量路由时所选路径的拥塞特征后,建立了流量分布的最小化路径代价和模型.在流量路由选择路径时,提出基于瓶颈链路的最小代价路径路由算法.在实际的网络拓扑和流量矩阵数据基础上对所提模型及算法进行了实验验证,结果显示:在网络负载较大时最大链路利用率相对于已有模型可降低近20%.     

DraLCD:一种新的数据中心流量工程方法

流量均衡是为了避免网络拥塞而作为流量工程中的路由优化目标提出来的,由于数据中心网络的流量特性,使得传统IP网络的流量工程方法不一定适合.为此,本文在SDN(Software Defined Network)的框架下,提出了一种基于链路关键度的自适应负载均衡流量工程方法:DraLCD(Dynamic Routing Algorithm based on Link Critical Degree).该方法通过对全局视图的网络管控,并充分利用了网络中存在的冗余路径,在完成细粒度流量均衡的同时,能够降低控制器的计算开销以及与交换机之间的通信开销,最终完成路由优化的目标.最后,基于DraLCD设计的原型系统,通过在Mininet仿真平台中部署并进行仿真实验,与现有的等开销多路径路由算法ECMP(Equal-Cost Multi-Path)以及GFF(Global First Fit)路由算法相比较,能够明显地提升网络性能.     

一种基于混沌蚂蚁群算法的系统参数辨识方法

提出了一种基于混沌蚂蚁群算法的控制系统辨识方法,这种方法在给定控制系统数学模型的条件下,将控制系统的参数辨识问题转化为参数的寻优问题,之后利用混沌蚂蚁群算法的全局优化搜索能力对问题进行求解.以典型控制系统为例进行了计算机仿真,实验结果表明,使用混沌蚂蚁群算法可以得到很好的参数估计结果.     

基于能效优化的WSNs多径流量分配路由算法

该文针对传感器节点能量受限的特点建立能效优化模型,该模型兼顾网络传输能耗和能耗均衡特性,以最大化网络节点总剩余能量和最小化剩余能量的方差为目标,通过合理分配多条路径的流量来优化网络能效。利用权衡评价函数实现了模型的求解,进而提出一种多径流量分配路由(MFAR)算法。仿真实验表明,该算法能够合理配置各路径流量,显著提高网络能量效率,达到在降低网络能耗的同时保证能耗分布均衡的目标。     

最小化平均跳数的WDM网络逻辑拓扑优化算法

对波长路由光网络中的逻辑拓扑设计问题进行了探讨,并选择最小化平均分组跳数作为优化目标.理论分析表明:最小化平均分组跳数对于同时优化网络的拥塞率下限、拥塞概率、平均时延以及波长数下限具有一定的作用.以此为基础,结合最小跳数算法的局限性,提出一种改进的最小化平均分组跳数的启发式算法,并以NSFNET为仿真网络,比较了该算法与最短路径算法(分布式Bellman-Ford算法)、最小跳数算法(Minimum Hop)两种常用的基础算法在拓扑设计中的性能优劣.     

基于最小干扰路由的流量工程动态路由算法研究

分析目前流量工程动态路由算法研究现状,以提高网络吞吐量为目标,提出一种改进的流量工程动态路由算法,综合考虑了网络拓扑和流量分布状况,提出分级的链路关键度定义,将流量工程目标有效转化为路径约束。仿真结果表明所提算法性能比Kodialam算法及其它几种典型的动态路由算法好。     

MPLS流量工程中的约束路由技术

传统的IP路由协议采用最短路径算法(SPF),极易造成网络的拥塞.流量工程是目前网络中实现负载均衡和提高网络性能的一个重要技术.文中简要介绍了MPLS流量工程,重点分析了MPLS流量工程中所使用的路由协议约束路由,给出了约束的计算方法以及路由度量选择的准则.     

基于改进萤火虫算法的WSN覆盖优化

针对无线传感器网络节点部署不均所导致的网络覆盖率较低问题,以无线传感器网络覆盖率最大化为目标,提出一种基于改进萤火虫算法(IFA)的网络覆盖优化方法。该方法运用佳点集方法初始化种群,提高种群的多样性,奠定全局搜索基础;利用具有非线性指数递减的变形Sigmoid函数作为惯性权重,平衡算法的全局搜索和局部开发能力;采用高斯扰动策略对个体位置扰动更新,避免算法早熟。仿真结果表明,该算法与人工鱼群算法(AFSA)、种子杂交粒子群算法(HSPSO)和混沌萤火虫算法(CGSO)相比,能有效提高网络覆盖率,使节点部署分布更均匀。     

基于混沌粒子群优化的图像相关匹配算法研究

该文将混沌优化搜索技术应用于粒子群优化算法(PSO),提出了一种基于混沌搜索的粒子群优化算法(CPSO),该算法利用了PSO算法的收敛快速性和混沌运动的遍历性、随机性等特点,采用混沌初始化粒子初始位置,在运行过程中根据粒子群适应度的方差来自适应混沌更新粒子位置.几种典型函数的测试结果表明:CPSO提高了对多维空间的全局搜索能力,并可以有效避免早熟现象.将该方法用于图像相关匹配算法,提出了一种新的基于CPSO的图像相关匹配算法.实验结果证明该方法对解决噪声情况下的图像匹配问题十分有效.     

Virtual machine placement optimizing to improve network performance in cloud data centers

With the wide application of virtualization technology in cloud data centers, how to effectively place virtual machine （VM） is becoming a major issue for cloud providers. The existing virtual machine placement （VMP） solutions are mainly to optimize server resources. However, they pay little consideration on network resources optimization, and they do not concern the impact of the network topology and the current network traffic. A multi-resource constraints VMP scheme is proposed. Firstly, the authors attempt to reduce the total communication traffic in the data center network, which is abstracted as a quadratic assignment problem; and then aim at optimizing network maximum link utilization （MLU）. On the condition of slight variation of the total traffic, minimizing MLU can balance network traffic distribution and reduce network congestion hotspots, a classic combinatorial optimization problem as well as NP-hard problem. Ant colony optimization and 2-opt local search are combined to solve the problem. Simulation shows that MLU is decreased by 20%, and the number of hot links is decreased by 37%.     

Throughput Gateways-Congestion Trade-Off in Designing Multi-Radio Wireless Networks

In Wireless Mesh Networks (WMNs), traffic is mainly routed by WMN Backbone (WMNB) between the mesh clients and the Internet and goes through mesh gateways. Since almost all traffic has to pass through one of the MGs, the network may be unexpectedly congested at one or more of them, even if every mesh router provides enough throughput capacity. In this paper, we address the problem of congestion of gateways while designing WMNs. We propose a simultaneous optimization of three competing objectives, namely network deployment cost, interference between network channels and congestion of gateways while guaranteeing full coverage for mesh clients. We tailor a nature inspired meta-heuristic algorithm to solve the model whereby, several trade-off solutions are provided to the network planner to choose from. A comparative experimental study with different key parameter settings is conducted to evaluate the performance of the model.     

基于混沌理论与改进回声状态网络的网络流量多步预测

网络流量预测是网络管理及网络拥塞控制的重要问题,针对该问题提出一种基于混沌理论与改进回声状态网络的网络流量预测方法。首先利用0-1混沌测试法与最大Lyapunov指数法对不同时间尺度下的网络流量样本数据进行分析,确定网络流量在不同时间尺度下都具有混沌特性。将相空间重构技术引入网络流量预测,通过C-C方法确定延迟时间,G-P算法确定嵌入维数。对网络流量时间序列进行相空间重构之后,利用一种改进的回声状态网络进行网络流量的多步预测。提出一种改进的和声搜索优化算法对回声状态网络的相关参数进行优化以提高预测精度。利用网络流量的公共数据集以及实际数据进行了仿真,结果表明,提出的预测方法具有更高的预测精度以及更小的预测误差。     

业务优先级感知的网络流量调度机制

针对网络中业务数据流过大、分布不均匀所造成的网络拥塞,提出一种优先级感知的动态网络流量调度机制.利用令牌桶算法,根据业务优先级的不同为不同业务分配不同速率的令牌,以实现业务优先级的划分;综合考虑业务的优先级及用户节点剩余缓存空间,对不同的业务采取不同的处理方式;同时,以流量到达因素、服务因素及节点缓存为指标定义了一种网络流量调度机制性能指标——分组丢失率.数值结果表明,所提机制可以对网络中业务优先级进行合理的划分,从而有效利用网络资源,预防网络拥塞,提升网络性能,为用户提供更加稳定可靠的网络服务.     

Dynamic burst discarding scheme for deflection routing in optical burst switching networks

This paper proposes a dynamic burst discarding scheme for deflection routing in optical burst switching networks. In general, deflection routing is effective in lightly loaded situations, whereas it has a contrary effect in congested networks because deflected bursts accelerate network congestion. Thus deflection routing should be employed in lightly loaded networks. Incoming traffic, however, varies in time and location, so that temporal and/or local congestion cannot be avoided. Our proposed scheme resolves this problem in the following way. Each node autonomously detects congestion with local information, and bursts to be deflected are discarded in a probabilistic manner, based on the degree of detected congestion and the numbers of elapsed and remaining hops of those bursts. Simulation experiments show that when congestion happens temporarily, the proposed scheme reduces the burst loss probability, and it utilizes network resources efficiently when local congestion happens.     

A Cooperative Differential Game Model for Multiuser Rate-Based Flow Control

Flow control is one typical resource management tool. Its objectives are to adjust the traffic in the network, and resolve data traffic congestion, maximize the utilization of available bandwidth resource and realize fairness among different sources. Taking more consideration on the interaction and the dynamic characteristics of the flow, in this paper, we propose a cooperative differential game of flow control. Our goal is to assign sources with appropriate transmission rate levels so as to the queue length in the bottleneck link is optimal for the network performance and their benefits are maximal. We derive a payment distribution mechanism that would constitute a time-consistent solution and guarantee individual rationality.     

Trunk congestion control in heterogeneous circuit switched networks

A circuit-switched network with two types of traffic is modeled as a finite two-dimensional Markov chain. The problem of trunk congestion under different routing schemes is analyzed. It is shown that the trunk reservation technique can be used to alleviate trunk congestion in this heterogeneous traffic environment. It is also shown that two control schemes, namely, the restricted access and preemption, when properly applied, may minimize the blocking of one type of traffic while keeping that of the other at a certain level. Some numerical examples are presented     

Taking advantage of ATM services and tariffs: the importance oftransport layer dynamic rate adaptation

Modern network services provided by frame relay (FR) or asynchronous transfer mode (ATM) networks show a wide variety of service characteristics and related quality of service, which amounts to a tremendous diversity of tariff structures. One of the network provider's objectives is to maximize the chargeable utilization of the network. This is intended to be achieved by a traffic contract on a per-connection basis. The network service user's interest is, of course, to minimize the cost for usage of the service. This can be achieved by traffic-contract-conformant behavior. In order to avoid (chargeable) injection of data that will be lost due to congestion in the network, the user has to adapt to the congestion state of the network by interpreting the congestion information provided by the network service. If the network user is logically mapped to the lowest end-to-end layer (i.e., the transport layer), the adaptive behavior has to be realized by adaptive rate control in this layer. This article analyzes the upcoming network services and their tariffs, demonstrates the advantage of rate control by a congestion avoidance algorithm, and the applicability of this concept to the telemetry and scientific data distribution applications of the European Space Agency (ESA)