基于跳数约束的R边连通网络设计

基于跳数约束的R边连通网络设计就是设计一个网络，且任意两点之间满足给定的边连通度及跳数要求，使得链路的总费用为最小。本文提出了一个启发式迭代求解该问题的算法。首先形成一个初始R边连通图。通过边交换来迭代降低边集的费用；最后增加一些边满足跳数约束，再通过边置换和边删除来降低费用得到一个较优的扩充图。     

面向LEO卫星网络的高效路由算法

由于卫星星上处理以及存储能力有限,随着卫星网络的规模越来越庞大,迫切需要一种简单高效的路由算法.为此,提出了一种基于网络拥塞程度感知的路由策略(Network Congestion-Aware Routing Algorithm,NCARA).NCARA路由策略在网络处于非拥塞状态时采用Dijkstra算法寻路,网络拥塞时换用改进广度优先搜索算法(Enhance Breadth First Search,en-BFS)寻找最短路径.en-BFS算法利用卫星网络拓扑呈二维网格拓扑的特征,将最小跳数作为主要衡量指标,选出最小跳数路径集合;然后将传输时延和传播时延作为衡量标准,以O(V+E)(V为图的节点个数,E为图的边的数目)的时间复杂度在最小跳数集合中选择出最小权值路径.最后通过数学方法证明了算法的正确性以及有效性.仿真结果表明,所提路由算法的平均时延、丢包率等都与传统算法相当,但是算法复杂度却得到极大的降低.     

基于带宽和跳数的流量工程动态路由选择算法研究

随着网络规模和网络硬件的快速发展,支持流量工程的路由器解决方案已经成为一种趋势,而流量工程动态路由选择算法则是流量工程方案的一个重要组成部分.本文分析了流量工程路由算法的研究现状,提出了以跳数和带宽作为量度的流量工程路由算法数学模型,并给出了路由算法规则.最后,通过计算机仿真验证了该算法的可行性和相对于只采用现行最短路径优先路由选择算法的优越性.     

不可分流网络的最小费用流问题

通常情况下单位流量费用最小的那条路径发送各个流总费用是最小的,但是往往单位流量费用最小的那条路径并不一定能满足所有流均可通过。针对不可分流的网络流最小费用问题,提出按流值排序寻求最优解的算法,并给出相关的理论证明及算法,最后通过具体实验测试了该算法的有效性。此算法可以快速求解所提的问题,并能够算出最优值。实例结果表明,该算法有效地解决了不可分流的网络流最小费用问题,可以应用于实际的网络优化中。     

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.     

无线自组织网络中一种拥塞意识的多径路由算法

提出了无线自组织网络中一种拥塞意识的多径路由算法。该算法在路由发现过程中,综合节点的队列长度和路径跳数来动态确定路由请求消息的转发概率,可以在保证路由请求消息有一定送达率的条件下,降低路由开销;在路径选择和流量分配过程中,综合考虑节点的队列长度和路径质量作为路由度量,发现流量高吞吐量低拥塞路径,并基于该度量值进行流量分配。仿真结果显示,所提出的多径路由算法能有效提高网络性能。     

基于最大公共路径匹配的拓扑推断算法

针对存在节点动态加入和退出的网络,提出了一种基于最大公共路径匹配的拓扑推断算法.该算法根据背景流量影响对“三明治”包中两个小包进行排序重组,利用重组后的“三明治”包对节点对相似度进行计算,以提高节点对相似度的估计精度;利用TTL跳数信息选择匹配路径,按照公共路径长度匹配搜索新加入节点的插入位置,减少测量过程中所需的探测次数,提高拓扑推断的效率.仿真结果表明,该算法能提高网络拓扑结构推断的准确性和效率.     

传感器网络中基于最短路径树的低延时节能路由算法

借助图论中最短路径和最小生成树的原理,在无线传感器网络中构建若干棵以Sink节点为根的最短路径源路由树。与最小生成树相比,最短路径树能保证路径上大部分节点找到节点间RSSI较强的通讯路径并以较少的跳数把数据传输给Sink节点,而最小生成树中的节点则需较多跳数。因此,提出的算法在一定程度上降低了延时。算法通过事先设定最低RSSI和节点最大剩余能量MRE来构建路由树,并修改已存在的路由算法,从而保证节点通讯的可靠性和网络的节能。     

全光网络中动态型波长路由算法的研究

分析了光路径的跳数（H）、拥挤程度（C）以及全网剩余波长总数（FW）对选路的影响,进而提出一种新型的动态波长路由算法。该算法利用网络中剩余资源的数量,动态调节选路策略,将业务分布在最短、负载最小以及剩余波长数和跳数比值最大的路径上;当有效资源减少时,增加最短路径选择的概率;当有效资源增加时,增加小负载路径的选择概率。计算机仿真结果表明,该算法的阻塞率比传统算法FAR和FPLC算法分别降低了19．1％和12．7％。     

基于DV-Hop算法的无线传感器网络定位精度优化

在无线传感器网络定位领域,DV-Hop算法因其实现简单得以广泛使用.针对DV-Hop算法定位误差较大的问题,提出一种基于DV-Hop多通信半径的加权定位算法.该算法利用多通信半径并通过引入修正因子细化和优化跳数,利用最小均方误差准则和加权方式修正平均跳距,并利用加权最小二乘法估算未知节点坐标.通过仿真得出所提算法在相同实验条件下的定位精度较DV-Hop算法提升约60.5％,相较于双通信半径优化算法和3-DV-Hop算法分别提升约36.4％和13.8％.     

A novel truncated approximation based algorithm for state estimation of discrete-time Markov jump linear systems

In this paper, state estimation problem for discrete-time Markov jump linear systems is considered. First, three equalities are proposed. Next, they are applied to the state estimation problem of considered systems so that a novel suboptimal algorithm in the sense of minimum mean-square error estimate is obtained where the computation and storage load of the suboptimal algorithm is not ever-increasing with the length of the noise observation sequence. The proposed algorithm and the suboptimal adaptive algorithm proposed in [1] are all based on a truncated approximation strategy. However, compared with the algorithm of [1], the proposed algorithm requires much less approximations. Computer simulations are carried out to evaluate the performance of the proposed algorithm.     

基于微分进化的信息物理融合系统网关优化部署方法

为解决信息物理融合系统下无线传感器网络接入互联网的问题,该文提出一种基于微分进化的网关优化部署方法。该方法以最小化网关覆盖半径和负载平衡水平为优化目标,利用微分进化算法寻找网关优化部署方案,通过自适应反向搜索、动态参数调整等方法保障寻优过程的种群多样性,解决几何 中心下的网关部署问题。仿真实验结果表明,该方法具备良好的全局寻优能力和收敛速度,能够在缩小网关集覆盖半径的前提下,进一步平衡各网关之间的负载水平,提高信息物理融合系统的网络QoS水平。     

Robust adaptive beamforming for large-scale arrays

For a large-scale adaptive array, heavy computational load and high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system. Moreover, the large-scale array becomes extremely sensitive to array imperfections. First, based on a restructured recursive linearly constrained minimum variance algorithm and a gradient-based optimization method, a new robust recursive linearly constrained minimum variance (RRLCMV) algorithm is proposed in this paper. The computational load of the RRLCMV algorithm is on the order of o(N), which is less than that of the conventional gradient-based robust adaptive algorithm. Then, a new efficient parallel robust recursive linearly constrained minimum variance (PRRLCMV) adaptive algorithm is proposed by appropriately partitioning the RRLCMV algorithm into a number of operational modules. It can be easily executed in a distributed-parallel-processing fashion, sequentially and in parallel. As a result, the PRRLCMV algorithm provides an effective solution that can alleviate the bottleneck of high-rate data transmission and reduce the computational cost. Finally, an implementation scheme of the PRRLCMV algorithm based on a distributed-parallel-processing system is also proposed. The simulation results demonstrate that the new PRRLCMV algorithm can significantly reduce the degradation due to various array errors.     

Research on switch migration method based on minimum cost path

In order to protect the controller,especially the controller in backbone network,from security threats and attacks,improve the security of the software-defined network (SDN) control plane,a switch migration algorithm based on minimum cost path was proposed.A load prediction module was added to the migration model,which executed a controller load prediction algorithm to obtain a load prediction matrix,and then a migration-target controller set was determined according to the load prediction matrix.The improved Dijkstra algorithm was used to determine the minimum cost path.According to the load state of the controller and the traffic priority of the switch to be migrated,the optimal migration switch set was determined.The problem of isolated nodes was solved that may occur during the migration process.The experimental results show that the migration timing of the algorithm is more reasonable,the selection of the migration controller and the target controller is more reasonable,the load balancing of the control plane is realized,the number of migrations and cost are reduced,and the performance of the controller is improved.     

A linear‐based trunk reservation routing algorithm for ATM networks

In this paper a practical routing algorithm is proposed that increases the network throughput irrespective of the network traffic load. Its effectiveness is based on an efficient cost function which achieves a successful trade‐off between the use of the minimum‐hop routes and the application of the load‐balancing concept. Moreover, it employs the known Trunk Reservation notion according to a probability that increases linearly with the traffic load. This results in an effective compromise of the performance of the algorithm between light and heavy traffic loads. Finally, its simplicity and its suitability for a real‐time application render it as an efficient routing algorithm for ATM networks. Copyright © 1999 John Wiley & Sons, Ltd.     

C-Si模型分子动力学三维并行仿真算法

对于单晶硅磨削过程模拟的并行算法,依据C-Si系统的分子动力学模型及其特殊模型的特性,通过分析负载均衡和消息通信,利用"最小表面"原则,给出了一种空间分解并行方案。仿真实验证明算法可以缓解负载失衡并且降低通信开销,收集的对比实验数据证实了算法的高效性。     

双通道旋转变压器解码算法改进

在某型测控设备天线控制单元维护过程中,发现天线转动时方位角存在跳码现象。针对该问题,文中通过分析天线角度采集与解码过程,发现当前所采用二进制组合编码的局限性,进一步对粗精码相位差超出可修正范围时出现跳码的原因进行理论分析,提出了改进的粗极余数与精极值组合算法。理论分析和仿真验证结果同时表明,新算法的纠错能力是二进制组合编码算法的2倍。     

Minimising the size of voids in optical packet switching using a novel packet scheduling algorithm

In this paper, we propose a new packet scheduling algorithm to minimise the size of voids in optical packet switching. The effects of excess load, output utilisation, and packet loss probability are closely studied. Other contributing factors to the packet loss probability, which include the buffer depth and the numbers of wavelength channels, are also investigated. The proposed algorithm is of importance to next generation networks where broadband capabilities with end-to-end quality of service over all-IP optical networks is envisaged.     

一种利用Gauss变异优化BP神经网络的方法

为了克服传统BP算法收敛速度慢和局部极小点等问题,提出了一种改进的BP网络训练方法,将改进的BP算法和遗传算法相结合。首先引入遗传算法中群体的概念,选取最好个体中的误差作为最小误差,其次利用Gauss变异生成的两个小随机数作为BP算法中的学习率和冲量系数,实现对两个参数的动态调整,以达到对BP网络的权值优化的目的。实验结果表明,该方法有效提高了BP网络的收敛速度,在训练时间方面具有明显的优越性,具有较好的实用性。     

异构无线网络业务接入多目标优化控制算法

提出了一种应用于异构无线网络环境的基于多目标优化的业务接入控制算法.该算法以业务占用总资源最少、业务阻塞率最低和网络间负载最均衡为目标建立了多目标优化控制模型,采用高斯和戒上型组合隶属函数将多目标问题模糊化,利用最大化满意度指标法将多目标问题转化为单目标问题,并通过遗传算法求得最优解.仿真结果表明,所提算法能在兼顾各网络资源高效利用的同时,保证业务接入的可靠性,并相对于参考算法有效降低了业务阻塞率.