最小代价多播生成树的快速算法

本文针对MPH（Minimum Path Cost Heuristic）等多播最小生成树算法存在的问题，通过改进最短路径节点的搜寻过程，以较小的存储空间为代价，获得了计算效率很高的快速最小代价多播生成树算法FMPH（Fast Minimum Path Cost Heuristic），且获得多播生成树与MPH算法完全相同，随机网络模型的仿真结果表明：FMPH算法快速、稳定，是一种值得推广使用的高效算法。     

加权的基于多播节点的多播路由算法

在许多多播应用中,降低多播树网络费用非常重要.本文提出了加权的基于多播节点的多播路由算法（WDDMC算法）.由于改变了DDMC（Destination-Driven routing for low-cost Multicast ）算法中的指示函数,适当降低了多播节点作为中间节点的优先级,提高非多播节点作为中间节点的优先级,从而使得多播树更接近最小Steiner树.在随机网络上的仿真结果表明,WDDMC算法的多播树网络费用优于DDMC算法.该算法的复杂度与DDMC算法完全相同.     

基于关键节点和多播节点的多播路由算法

在视频会议等多播应用中，降低多播树网络费用非常重要。本文提出了基于关键节点和目的节点的多播路由KDDMC算法。由于在算法中优先考虑采用关键节点，实现更多链路的共享，从而降低网络费用。在随机网络上的仿真结果表明，KDDMC算法的多播树网络费用优于SPH算法。同时证明了KDDMC算法的复杂度为O(n^3)，且利用所提出的路由表算法易于分布式实现。     

一种基于蚁群算法的分布式多播路由算法

随着计算机网络的不断发展,大量多媒体应用要求网络具有满足QoS约束的多播功能.应用多播的关键是确定有效的多播路由,即求解最优Steiner树.目前提出的大部分都是集中式的或本质上是集中式的启发式算法,关于分布式算法的研究还比较少.本文提出了一种基于蚁群算法的分布式多播路由算法.该算法在源节点不掌握整个网络信息的情况下,利用网络的局部启发式信息和蚂蚁留下的信息素建立最优的多播路由.结合多播路由问题的特点,对算法进行了改进,使算法的收敛速度和解的质量都得到了较大的提高.仿真实验结果验证了该算法的有效性.     

多材料Terminal Steiner树拼接问题的近似算法研究

在赋权连通网络下,给定多种材料及每种材料的费用和拼接费用,以便寻找赋权网络中的一棵Terminal Steiner树,并用给定材料连接此树,使得总费用及材料根数达到最小,记此问题为多材料Terminal Steiner树拼接问题。为了解决Terminal Steiner树拼接问题,首先分析Terminal Steiner树拼接问题是NP问题,不存在多项式时间算法;然后基于Steiner树问题和变尺寸装箱问题的近似算法及算法复杂度,给出多材料的Terminal Steiner树拼接问题的一个近似算法;最后证明算法的近似值及近似算法的时间复杂度。     

Ad Hoc多播路由协议研究与实现

文中研究了一种基于分割树的移动Ad Hoc网络（MANET）多播路由协议（TPBOM）,该协议中,信源基于成员节点的定位信息创建一个Steiner树覆盖图,为满足可扩展性的要求,信源利用最大权反向分割（MHRTP）的树分割算法将其分割为若干个区,并将每个区封装进一个树分发数据包中,以便将所创建的Steiner树分发至所有成员节点,封装的数据包中不包含目的地址列表,数据则沿该Steiner树进行传输,仿真实现表明,TPBOM在可扩展的多播群中获得了较高的性能。     

基于直角Steiner树的片上网络互连算法

提出了一种基于最小直角Steiner树,在Manhattan平面上避免障碍物的互连算法,以实现片上网络中各IP核的互连.该算法在定制NoC中将Steiner树的生成算法用于互连设计.算法首先在初始阶段对有障碍两点间的边权重重新赋值,然后调用最小生成树算法,使生成的直角Steiner树总长度最小.实验表明,该算法可以使片上网络的总连线缩短.     

一种路径对约束下构造最低代价我播树的探索算法

提出了一种新的探索算法,它根据源与目的节点的时延约束,构造最低代价的多播树。并且可以在网络节点请求加入或离开时,通过更新现有的多播树,实现多播的动态维护。对该算法进行了仿真,并与现有的一些算法进行了比较。     

无线Ad Hoc网络Steiner树实现协议研究

针对无线Ad hoc网络多跳,拓扑结构随时可能动态变化,协作节点间数据传输需实时性强等问题,利用Netlog语言宣告声明最小Steiner树协议的构造算法方法适应解决。协议可快速构造一棵近似最小的Steiner树,每个节点独立运行声明Steiner树协议,构造Steiner节点间的虚拟全联通网络,在此网络上构造最小代价生成树;然后将此树的节点与边对应原网络的节点和边,继续构造最小代价生成树,最后将此树上的非Steiner节点的叶子节点删除,近似得到最小代价Steiner树,该方法在实验平台上得以验证,为无线移动网络中资源的选择利用提供了一种新的可尝试性的新方法。     

在overlay网络上的负载平衡多播路由算法

针对基于代理服务器的overlay网络的负载平衡多播路由算法被提出.它能均衡利用overlay网络的有限资源,并能满足多播应用的延迟限制需求.首先用具有延迟约束的Steiner树问题对路由问题进行建模;然后采用预计算方法将计算复杂度集中在预备的单点路径计算上,使由这些单点路径所构成的网络更易于构建负载平衡路由树:预计算只计算一次,结果使用多次,因此降低了总体的计算复杂度.仿真实验的结果表明,相对于其他的快速启发式算法,该算法能提供更为优越的性能.整体而言,基于预计算的负载平衡多播路由算法在性能和计算复杂度方面取得了很好的平衡.     

基于可视化试验的Exp-Geo算法

全局最短路径是组合优化的经典问题之一。求解最小Steiner树的可视化试验成功的在给定节点中间生成了Steiner点,但当给定节点数目增多且呈不规则分布时,试验方法形成薄膜路径困难并且不稳定。针对试验的不足,文中构建了Exp-Geo算法。在给定点数目增多时,采用该算法能够在给定节点之间生成Steiner点,得到全局最短路径,弥补试验的不足。经过多次试验、计算、对比分析,证明该算法能在多点系统中找到系统全局最短路径,为可视化试验的推广奠定了基础。     

基于树型编码的MRST混合遗传算法及其并行处理

提出一个关于最小矩形边斯坦纳树（ＭＲＳＴ）的混合遗传算法。该算法根据ＭＲＳＴ问题的特点,采用了树形结构编程方案以及相应的遗传操作方法,在群体设定时均匀划分空间,依据遗传群体的环境参量动态地调整遗传算法的进化策略;在执行遗传操作时与爬山法相结合,在群体更新时引进模拟退火更新机制,大大加强其寻优能力。最后,提出了该算法基于ＭＩＭＤ模型的扩展分布式并行算法。算法复杂性分析以及实验结果表明该算法有效。     

Multicriteria Steiner tree with the cost of Steiner vertices

The multicriteria problem of constructing the Steiner tree with consideration for the cost of additional Steiner vertices is studied. Formulations of the problems of constructing the covering Steiner trees and algorithmic approaches are described. The engineering formulation of the problem is aimed at constructing a telecommunications network with allowance for the spatial distribution of radio interferences. An approach to solving the formulated milticriterion problem on the basis of combination of two solving schemes is proposed: (1) the basic scheme for constructing a covering Steiner tree on the basis of clustering the vertices of the initial graph and (2) the general scheme for constructing the covering Steiner trees with allowance for the number of additional vertices and calculation of the Pareto-efficient solutions. A module based on the modified Prim’s algorithm for constructing a multicriteria covering tree is additionally used. The vertices of the initial graph are clustered on the basis of a hierarchical algorithm. Examples of a computational experiment on constructing the multicriteria Steiner trees are given.     

共享路径优先组播路由算法

求解开销最小组播树在数学上归结为Steiner树问题,但由于寻找最优的Steiner树问题是NP-Complete问题,因此在组播应用中,采用启发式算法获得次优的组播树是常见的方法。该文提出了一种新的的启发式组播路由算法(Shared Path First Heuristic,SPFH)该算法在选择目的节点加入组播树时,既考虑到目的节点到树上的距离,又考虑到先加入的节点对后续加入节点的影响。算法从距离当前组播树近的目的节点中挑选节点加入组播树,选择的规则是,把能够减小其它目的节点加入组播树开销的节点先加入树。仿真结果表明,SPFH算法能找到开销接近于最优解的组播树。     

A heuristic for constructing a rectilinear Steiner tree by reusing routing resources over obstacles

The obstacle-avoiding rectilinear Steiner minimal tree (OARSMT) problem is a hot topic in very-large-scale integration physical design. In practice, most of the obstacles occupy the device layer and certain lower metal layers. Therefore, we can place wires on top of the obstacles. To maximize routing resources over obstacles, we propose a heuristic for constructing a rectilinear Steiner tree with slew constraints. Our algorithm adopts an extended rectilinear full Steiner tree grid as the routing graph. We mark two types of Steiner point candidates, which are used for constructing Steiner trees and refining solutions. A shortest path heuristic variant is designed for constructing Steiner trees and it takes into account slew constraint by inhibiting growth. Furthermore, we use a pre-computed strategy to avoid calculating slew rate repeatedly. Experimental results show that our algorithm maximizes routing resources over obstacles and saves routing resources outside obstacles. Compared with the conventional OARSMT algorithm, our algorithm reduces the wire length outside obstacles by as much as 18.74% and total wire length by as much as 6.03%. Our algorithm improves the latest related algorithm by approximately 2% in terms of wire length within a reasonable running time. Additionally, calculating the slew rate only accounts for approximately 15% of the total runing time.     

Maze Routing Steiner Trees With Delay Versus Wire Length Tradeoff

In this paper, we address the problem of generating good topologies of rectilinear Steiner trees using path search algorithms. Various techniques have been applied in order to achieve acceptable run times on a Maze Router that builds Steiner trees. A biasing technique proposed for wire length improvement, produces trees that are within 2% from optimal topologies in average. By introducing a sharing factor and a path-length factor we show how to trade-off wire length for delay. Experimental results show that our algorithm generates topologies with better delay compared to state of the art heuristics for Steiner trees, such as AHHK (from 26% to 40%) and P-Trees (from 1% to 30% and from 6% to 21% in the presence of blockages) while keeping the properties of a routing algorithm. An important motivation for this work lies in the fact that it can be used for estimation in the early stages as well as for actual routing, thereby improving the convergence and timing closure of the design significantly. We also provide some valuable theoretical background and insights on delay optimization and on how it relates to our maze router implementation.      

遗传算法与蚁群算法在商旅问题中的应用研究

遗传算法在多个领域得到了应用,如人工智能领域,最优化求解问题,TSP问题等等.本文就遗传算法的基本定义与思想进行了介绍,同时介绍了由遗传算法优化或者衍生而来的一些算法的作用.并介绍了遗传算法的具体应用.     

基于量子遗传算法和IMST算法的QoS多播路由算法

本文提出了一种求解QoS多播路由算法,该算法基于量子遗传算法(Quantum Genetic Algorithm ,QGA)和IMST算法(Improved Minimum Spanning Tree,IMST),首先在量子个体上实施量子交叉,这一操作有利于保留相对较好的基因段;其次,采用量子比特相位法更新量子门和自适应调整搜索网格的策略,使得种群的多样性强;最后,引入改进的MST算法进行受约束最小Steiner 树的生成,解的收敛精度高,收敛速度快;通过仿真实验标明此算法在种群规模较小,迭代次数较少的情况下就可以收敛到最优解,该算法的优化质量和效率都强于传统遗传算法和量子遗传算法.     

Multicast tree generation in networks with asymmetric links

We formulate the problem of multicast tree generation as one of computing a directed Steiner tree of minimal cost. In this context, we present a polynomial-time algorithm that provides for trade-off selection, using a single parameter κ, between the tree-cost (Steiner cost) and the run time efficiency. Further, the same algorithm may be used for delay optimization or tree-cost minimization simply by configuring the value of κ appropriately. We present theoretical and experimental analysis characterizing the problem and the performance of our algorithm. Theoretically, we show that it is highly unlikely that there exists a polynomial-time algorithm with a performance guarantee of constant times optimum cost, introduce metrics for measuring the asymmetry of graphs, and show that the worst-case cost of the tree produced by our algorithm is, at most, twice the optimum cost times the asymmetry, for two of these asymmetry metrics. For graphs with bounded asymmetry, this gives constant times optimum performance guarantee. We also show that three well-known algorithms for (undirected) Steiner trees are but particular cases of our algorithm. Our experimental study shows that operating at a low κ gives nearly best possible expected tree cost while maintaining acceptable run-time efficiency