基于代理的QoS组播路由算法

提出了一种基于代理（Agent)的QoS组播路由算法,它根据一个在网络中漫游的移动代理收集的网络状态来建立保证QoS的组播树,仿真实验表明,该算法是有效的和可行的。     

IP组播路由协议的研究与实现

概述了组播路由协议，分析了协议独立的组播路由－稀疏模式（PIM－SM）的缺陷，提出多个会聚点（RPs)的PIM－SM的改进机制，多个RPs机制有效地提高了原有单个RP的PIM－SM协议的健壮性，有利于实现负载均衡、分类业务及提高系统的容错性能，并讨论多个RPs机制的开销问题。分析了PIM－SM实现细节和组播技术的前景。     

基于模拟退火法的组播路由算法(英文)

本文提出了一种基于模拟退火算法的延时约束最小代价组播路由算法(SADLMA)。首先,本算法使用Dijkstra第K最短路算法建立了从源节点到每个目的节点的候选集。然后生成了相应的邻居结构。当温度下降时,根据接收概率从邻居结构里把新解选择出来,并且代替旧解。仿真试验表明本算法对实际网络是有效的。     

共享存储器ATM交换机组播路由方法

提出了在Ｎ＊Ｎ共享存储ＡＴＭ交换机上增加一条高速总线的方法,使其专用于组播路由,构成Ｎ＊Ｎ＋１ＡＴＭ交换机。虽增加少许硬件,但在不增加存储器尺寸及苛求存储器速度条件下,保持了共享存储器ＡＴＭ交换吞吐率高、信元丢失率低、易于管理突发业务等特点,同时增添了共享总线ＡＴＭ交换 机易于实现组播路由的优点,软件仿真证实,该方法提高了系统的性能,尤其适用于混合业务流。     

基于神经网络的组播路由调度方法

针对在高速包交换计算机网络中端到端时延及时延抖动限制的组播路由问题，提出了基于Ｈｏｐｆｉｅｌｄ神经网络的组播路由优化算法。实验表明，本算法能根据组播应用对时延及时延抖动限制的要求，快速，有效地构造最优组播树，有较强的实时性。     

基于广播中继的自组网组播路由协议改进(ODMRP-MPR)

提出一种对ODMRP协议的改进,即ODMRP-MPR路由协议。该协议继承了ODMRP协议对拓扑频繁变化的良好适应性,并采用广播中继机制MPR(Multipoint Relay),优化了组播转发网格并减少了协议开销,提高了协议对网络规模的可扩展性和吞吐量,并且提供拥塞控制,有效地解决单向链路问题,增强了协议的健壮性。通过对ODMRP-MPR和ODMRP协议的模拟仿真实验比较,验证了ODMRP-MPR协议的改进效果。     

基于动态代理选择的移动网络组播

针对移动网络组播面临的接入点间切换造成组播树频繁重构的问题,提出了一种新的移动网络组播方法DMA(Dynamic Multicast Agent)。DMA在远程加入的基础上,使用动态选择组播代理和局部隧道的方法,为移动网络内的节点提供组播服务。分析与仿真结果表明,DMA不但减少了因移动网络附着点改变而造成的组播树重构次数,在一定程度上屏蔽了移动网络的移动性对组播树造成的影响,而且使得组播数据总是能够以“接近最优”的路径进行转发。     

应用层组播路由的一种改进神经网络解法

研究了使用双层递归神经网络(DRNN)模型求解应用层组播路由的问题.对原有模型的神经元矩阵及能量函数进行改变,并引入了新的线性编程神经元,解决了原模型不能求解组播路由的缺陷.与启发式组播路由算法相比,该解决方案的计算复杂度低,速度较快,而且与其它的神经网络相比,由于引入了基尔霍夫限制条件,保障了解的质量,且所使用的神经元数量少,而在解的精确度上则与其它算法相当.     

多波长光网络的动态路由等效算法

针对多波长光网络的特点，提出了一种动态路由和波长分配的等效算法。采用波长图、增加虚拟源节点和目的节点等技术，把多波长网络转化为等效的单波长网络，避免了求解路由和波长分配两个复杂子问题，简化了算法的程序设计。利用最短径算法进行路由和波长分配可以求得问题的最优解，从而有效地降低了网络阻塞率。仿真结果表明：与FAR-2D算法相比，在4和8波长的全波长转换网络中，采用等效算法阻塞率最大降幅分别达到0．02、0．025。     

解析HGTPA的一种启发式组卷算法

组卷算法是在线考试系统的核心,本文结合遗传算法的优点,提出一种新的启发式遗传组卷算法(Heuristic Genetic Test Paper Algorithm,HGTPA),该算法能克服遗传算法的缺点,并在实验测试中取得比较满意的结果。     

一种ATM网络中的动态路由算法

针对前期工作中讨论的多阶段虚通道（ＶＰ）控制和ＶＰ拓扑优化问题，以及基于在每一个源目（ＳＤ）节点对之间存在一组备选路由集这一假设的相应的优化算法，提出了一个补充算法，它能够求出任意两节点间的所有可能路径。在此基础上，进一步研究了一种动态虚通路（ＶＣ）路由策略。与其它路由策略不同，它是在更一般的网络环境中加以考虑的。最后，给出了一个动态ＶＰ路由算法，这是动态ＶＣ路由策略中的一个重要组成部分。理论分析和试验结果表明，这些算法是正确的，且有极高的实用价值。     

A Nonuniform Clustering Routing Algorithm Based on an Improved K-Means Algorithm

In a large-scale wireless sensor network (WSN), densely distributed sensor nodes process a large amount of data. The aggregation of data in a network can consume a great amount of energy. To balance and reduce the energy consumption of nodes in a WSN and extend the network life, this paper proposes a nonuniform clustering routing algorithm based on the improved K-means algorithm. The algorithm uses a clustering method to form and optimize clusters, and it selects appropriate cluster heads to balance network energy consumption and extend the life cycle of the WSN. To ensure that the cluster head (CH) selection in the network is fair and that the location of the selected CH is not concentrated within a certain range, we chose the appropriate CH competition radius. Simulation results show that, compared with LEACH, LEACH-C, and the DEEC clustering algorithm, this algorithm can effectively balance the energy consumption of the CH and extend the network life.     

A Hybrid Genetic Algorithm for Vehicle Routing Problem with Complex Constraints

Most research on the Vehicle Routing Problem （VRP） is focused on standard conditions, which is not suitable for specific cases. A Hybrid Genetic Algorithm is proposed to solve a Vehicle Routing Problem （VRP） with complex side constraints. A novel coding method is designed especially for side constraints. A greedy algorithm combined with a random algorithm is introduced to enable the diversity of the initial population, as well as a local optimization algorithm employed to improve the searching efficiency. In order to evaluate the performance, this mechanism has been implemented in an oil distribution center, the experimental and executing results show that the near global optimal solution can be easily and quickly obtained by this method, and the solution is definitely satisfactory in the VRP application.     

物流车辆路径问题的混合快速蚂蚁算法

通过分析快速蚂蚁算法的原理和易陷入局部最优的缺点,提出了将贪婪算法和快速蚂蚁算法相结合的混合算法求解物流车辆路径问题.混合算法在最优值未改进次数超过限定次数时,自动调用贪婪算法来寻找一个局部最优解,并调整相应路径上信息素的量.为保证解的多样性,对贪婪算法本身使用随机选择第一个客户的方法进行了调整.用计算实例比较并分析了快速蚂蚁算法、混合算法及其他算法应用到车辆路径问题上的结果,说明了贪婪算法使混合算法跳出局部最优的过程以及混合算法的不足之处.     

基于启发式搜索策略的测试选择问题研究

测试选择是测试性设计的最基本步骤之一，本文通过对其数学模型的研究，构造了衡量测试集优劣程度的启发式函数，并由此实现了一种用于测试选择的遗传搜索算法。实例验证表明了该启发式函数的有效性，为测试性设计提供了一个简单有效的方法。     

基于混合粒子群算法的物流配送路径优化问题研究

针对物流配送路径优化问题,提出了一种融合Powell局部寻优算法和模拟退火算法的混合粒子群算法,以克服单用粒子群算法求解问题早熟收敛的不足,增加算法的开发能力,提高算法的全局搜索能力,并进行了实验计算.计算结果表明,用混合粒子群算法求解物流配送路径优化问题,可以在一定程度上提高粒子群算法在局部搜索能力和搜索全局最优解概率,从而得到质量较高的解.     

Single Failure Routing Protection Algorithm in the Hybrid SDN Network

Loop free alternate (LFA) is a routing protection scheme that is currently deployed in commercial routers. However, LFA cannot handle all single network component failure scenarios in traditional networks. As Internet service providers have begun to deploy software defined network (SDN) technology, the Internet will be in a hybrid SDN network where traditional and SDN devices coexist for a long time. Therefore, this study aims to deploy the LFA scheme in hybrid SDN network architecture to handle all possible single network component failure scenarios. First, the deployment of LFA scheme in a hybrid SDN network is described as a 0-1 integer linear programming (ILP) problem. Then, two greedy algorithms, namely, greedy algorithm for LFA based on hybrid SDN (GALFAHSDN) and improved greedy algorithm for LFA based on hybrid SDN (IGALFAHSDN), are proposed to solve the proposed problem. Finally, both algorithms are tested in the simulation environment and the real platform. Experiment results show that GALFAHSDN and IGALFAHSDN can cope with all single network component failure scenarios when only a small number of nodes are upgraded to SDN nodes. The path stretch of the two algorithms is less than 1.36.     

Ant Colony Optimization for Multi-Objective Multicast Routing

In the distributed networks, many applications send information from a sourcenode to multiple destination nodes. To support these applications requirements, the paper presents a multi-objective algorithm based on ant colonies to construct a multicast tree for data transmission in a computer network. The proposed algorithm simultaneously optimizes total weight (cost, delay and hop) of the multicast tree. Experimental results prove the proposed algorithm outperforms a recently published Multi-objective Multicast Algorithm specially designed for solving the multicast routing problem. Also, it is able to find a better solution with fast convergence speed and high reliability.