An orthogonal genetic algorithm for multimedia multicast routing

Many multimedia communication applications require a source to send multimedia information to multiple destinations through a communication network. To support these applications, it is necessary to determine a multicast tree of minimal cost to connect the source node to the destination nodes subject to delay constraints on multimedia communication. This problem is known as multimedia multicast routing and has been proved to be NP-complete. The paper proposes an orthogonal genetic algorithm for multimedia multicast routing. Its salient feature is to incorporate an experimental design method called orthogonal design into the crossover operation. As a result, it can search the solution space in a statistically sound manner and it is well suited for parallel implementation and execution. We execute the orthogonal genetic algorithm to solve two sets of benchmark test problems. The results indicate that for practical problem sizes, the orthogonal genetic algorithm can find near optimal solutions within moderate numbers of generations     

面向无线内容分发网络的树形拓扑生成算法

在无线内容分发网络中,为减轻骨干网络的传输压力,可将网络拓扑结构构建为以基站和Wi Fi接入点为根的若干棵最小生成树,并对生成树的深度和每个节点的度数进行约束。这种深度和度数约束的最小生成树问题是一个NP完全问题。针对该问题,首先提出能够生成优质近似解的启发式算法,该算法在不违反深度以及度数约束的情况下构建生成树,算法思想为在服务性节点相连的边中选择与当前生成树相连且权值最小的边加入生成树。然后在生成初始近似解的基础上采用定制的禁忌搜索算法和模拟退火算法对该近似解实施进一步优化。实验结果表明,在给定的约束条件下,禁忌搜索算法求得的解优于现有的遗传算法,在深度约束为4以及度数约束为10的条件下,解的改进幅度可达18.5%,所提算法的运行速度比遗传算法提高了10倍。     

基于遗传算法的可扩展应用层组播树构建

在应用层组播中,为降低节点的路径延时,通常采用遗传算法和启发式算法来减小组播树直径的方法,但在组播树具有大规模节点数时,遗传算法收敛时间长,而采用启发式算法难以在有约束条件下达到全局最优.本文在具有超节点的双层应用层组播模型基础上,提出了利用遗传算法构建出度受限最小带权路径延时生成树（MWPL-DC-ST）的生成算法GA-MWPL-DC-ST,利用该算法可在超节点上对双层组播树进行分布式构建,从而将求最优解问题的巨大计算量分担到多个超节点上.算法中的初始化、杂交和变异阶段采用启发式算法,对变异参数进行适应性调整,加快了算法的收敛速度.仿真试验表明,本文提出的双层应用层组播模型和GA-MWPL-DC-ST算法能得到比启发式算法更优的解,与采用单层模型的遗传算法相比较,显著降低了算法收敛时间,解决了遗传算法构建有大规模节点数的应用层组播树的可扩展性问题.     

Optimizing I/O server placement for parallel I/O on switch-based irregular networks

In this paper, we study I/O server placement for optimizing parallel I/O performance on switch-based clusters, which typically adopt irregular network topologies to allow construction of scalable systems with incremental expansion capability. Finding optimal solution to this problem is computationally intractable. We quantified the number of messages travelling through each network link by a workload function, and developed three heuristic algorithms to find good solutions based on the values of the workload function. The maximum-workload-based heuristic chooses the locations for I/O nodes in order to minimize the maximum value of the workload function. The distance-based heuristic aims to minimize the average distance between the compute nodes and I/O nodes, which is equivalent to minimizing average workload on the network links. The load-balance-based heuristic balances the workload on the links based on a recursive traversal of the routing tree for the network. Our simulation results demonstrate performance advantage of our algorithms over a number of algorithms commonly used in existing parallel systems. In particular, the load-balance-based algorithm is superior to the other algorithms in most cases, with improvement ratio of 10 to 95% in terms of parallel I/O throughput.     

The class Steiner minimal tree problem: a lower bound and test problem generation

The class Steiner minimal tree problem is an extension of the standard Steiner minimal tree problem in graphs, motivated by the problem of wire routing in the area of physical design of very large scale integration (VLSI). This problem is NP-hard, even if there are no Steiner nodes and the graph is a tree; moreover, there exists no polynomial time approximation algorithm with a constant bound on the relative error under the hypothesis that P NP [16]. Hence, fast and good heuristic algorithms are needed in practice. In this paper, we present an integer programming formulation of the problem. Using Lagrangean relaxation and subgradient optimization, we derive a lower bound. In order to test the lower bound, we present a procedure for generating test problems for the class Steiner minimal tree problem that have known optimal solutions. The computational experiments for the test problems demonstrate that the lower bound is very tight and differs from the optimal solutions by only a few percent on average for sparse graphs. Received: 5 July 1999 / Revised version: 14 July 2000     

枚举单体型组装问题多个最优解的遗传算法设计

单体型组装问题就是根据个体基因组测序获得的DNA序列数据重构出该个体的一对单体型。目前单体型组装问题的各种优化计算模型已有相关的启发式算法和参数化精确算法,但是这些算法只能得出一个最优解,即一对单体型。可是生物问题的最优解往往不是唯一的,或者真实解可能只是接近最优的。该文设计了一个新的能枚举出最优的多个解的遗传算法。实验结果表明该算法具有较高的单体型重建精度,并为生物学家根据领域知识在算法获得的多个解的基础进一步选择提供了可能。     

基于服务质量的多媒体通信初始路由建立算法的研究

基于服务质量的路由选择机制是从根本上提供分布式多媒体应用所需的服务质量保证的重要手段之一。该文提出了两种基于服务质量的多媒体通信初始路由建立算法。一种算法支持在两个通信方之间建立基于服务质量的初始路由,既可以作为点对点多媒体通信的基于服务质量的路由选择／初始路由建立算法,也可以作为初始成员为两个的多媒体动态组通信的基于服务质量的初始路由建立算法,另一种算法支持在多个通信方之间建立基于服务质量的初始路由,既可以作为多媒体静态组通信的基于服务质量的路由选择／初始路由建立算法,也可以作为初始成员为多个的多媒体动态组通信的基于服务质量的初始路由建立算法,文中还探讨了这两种算法的正确性。     

并行机间歇过程生产调度的遗传局部搜索算法

研究了一类集成分批的并行机间歇过程调度问题(parallel machine batch process scheduling problem,简称PBPSP),将此问题转化为固定费用运输问题(6xed charge transportation problem,简称FCTP)后,提出了具有集中邻域搜索机制和局部最优逃逸机制的遗传局部搜索算法(genetic local search algorithm,简称GLSA).GLSA算法用先根遍历边排列模式编码生成树解,具有高效的子树补充式单点交叉操作.将基于网络单纯型方法的邻域搜索作为变异算子,并提出了连续随机节点邻域搜索的集中邻域搜索策略以及随机旋转变异与全局邻域搜索相结合的局部最优逃逸策略,极大地强化了遗传局部搜索算法的全局寻优能力.实验表明:GLSA算法获得的解质量优于基于排列编码的遗传算法和基于矩阵编码的遗传算法,得到了所有Benchmark问题的最优解,且具有高鲁棒性.针对一定规模的FCTP问题,GLSA算法比Tabu启发式搜索算法具有更高的获得最优解几率.     

A note on distributed multicast routing in point-to-point networks

The distributed algorithm for a multicast connection set-up, based on the ‘cheapest insertion’ heuristic, is reviewed. The multicast routing problem is translated into a Steiner tree problem in point-to-point networks where nodes have only a limited knowledge about the network. A solution is proposed in which the time complexity and the amount of information exchanged between network nodes are proportional to the number of members of the multicast group. The Steiner tree is constructed by means of a distributed table-passing algorithm. The analysis of the algorithm presented, backed up by simulation results, confirms its superiority over the algorithm based on ‘waving technique’.Scope and purposeMulticasting is a mechanism used in communication networks that allows distribution of information from a single source to multiple destinations. The problem of finding a multicast connection for a static group of communicating entities in connection-oriented point-to-point network can be formulated in graph theory as a minimum Steiner tree problem. Due to NP-completeness of the Steiner tree problem multicast, routing algorithms are based on heuristics. The diversity of network environments and the lack of centralised information about network topology require an effective distribution of the multicast routing algorithms among the network nodes. This article presents an alternative to the distributed algorithm proposed by Rugelj and Klavzar that implements the same heuristics for the construction of a minimum cost multicast connection in point-to-point networks. The present algorithm constitutes a substantial improvement over that previously proposed with regard to running time and the amount of the information exchanged between network nodes.     

物流网络中节点带权的Steiner最小树的参数算法

通过优化物流的运输网络,可以有效地降低物流成本。集中配送的物流网络优化问题可以转换成求解节点带权的Steiner最小树问题,这是一个NP-hard问题。运用参数理论,提出一种新的启发式解决算法P-NSMT。算法的思想是：首先尽可能只利用终端节点构造一棵连通的最小生成树,然后逐步向树中添加能减少生成树总权值的Steiner节点,最终生成一棵节点总数不超过参数k的Steiner最小树。实验表明,与同类型其他算法相比,P-NSMT算法具有更好的准确性和时间效率,特别适应于网络规模大、终端配送节点数目较少的物流网络。     

多源多播服务功能链优化部署算法

在软件定义网络和网络功能虚拟化环境下,针对多播中的服务功能链（SFC）部署,探究了多源多播中的联合虚拟网络功能（VNF）部署和流量路由问题,目的是最小化节点资源消耗和链路资源消耗总成本。同时考虑到节点、链路及带宽延迟限制,建立了整数线性规划模型,并提出一种名为多源多播树优化的启发式算法。该算法旨在为所有用户找到最近的源节点,获得多个源、目节点组,为每个组构造一棵多播服务功能树,然后优化多播服务功能树。实验仿真结果表明,与其他启发式算法相比,该算法有效地降低了总成本、链路利用率及时延。     

Optimal multicast routing with quality of service constraints

We consider the problem of optimal multicast routing with Quality of Service constraints motivated by the requirements of interactive continuous media communication, e.g., real-time teleconferencing. We concentrate on distributed algorithms for determining a tree over the network topology, rooted at the source and spanning the intended destinations. Quality of Service requirements for interactive continuous media typically impose constraints on some metric over the individual paths from the source to each destination, usually in the form of an upper bound on the delay. Thus, we focus on the problem of minimizing the cost of the tree while at the same time satisfying a common constraint over individual source-destination paths. We have shown that this problem is intractable, but have also devised centralized polynomial time heuristics that perform well. Here we present distributed algorithms to minimize tree cost while satisfying the constraints on the paths from the source to each destination.     

Ad hoc网络时延受限的Steiner树启发式算法

针对Ad hoc网络时延受限的Steiner树问题,设计一个分布式的快速启发式算法DCST,该算法通过对网络中节点进行标号,并根据标号修改节点间的关联关系,建立一棵时延受限的Steiner树。在网络节点保持时间同步的前提下,算法的时间复杂度为O(n)。与现有经典的Steiner树算法相比,该算法具有明显优势。     

Using genetic algorithms to design mesh networks

Designs for mesh communication networks must meet conflicting, interdependent requirements. This sets the stage for a complex problem with a solution that targets optimal topological connections, routing, and link capacity assignments. These assignments must minimize cost while satisfying traffic requirements and keeping network delays within permissible values. Since such a problem is NP-complete, developers must use heuristic techniques to handle the complexity and solve practical problems with a modest number of nodes. One heuristic technique, genetic algorithms, appears to be ideal to handle the design of mesh networks with capability of handling discrete values, multiobjective functions, and multiconstraint problems. Existing applications of genetic algorithms to this problem, however, have only optimized the network topology. They ignore the difficult subproblems of routing and capacity assignment, a crucial determiner of network quality and cost. This article presents a total solution to mesh network design using a genetic algorithm approach. The application is a 10-city network that links Hong Kong and nine other cities in China. The development demonstrates that this method can be used for networks of reasonable size with realistic topology and traffic requirements     

Contraflow Transportation Network Reconfiguration for Evacuation Route Planning

Given a transportation network having source nodes with evacuees and destination nodes, we want to find a contraflow network configuration, i.e., ideal direction for each edge, to minimize evacuation time. Contraflow is considered a potential remedy to reduce congestion during evacuations in the context of homeland security and natural disasters (e.g., hurricanes). This problem is computationally challenging because of the very large search space and the expensive calculation of evacuation time on a given network. To our knowledge, this paper presents the first macroscopic approaches for the solution of contraflow network reconfiguration incorporating road capacity constraints, multiple sources, congestion factor, and scalability. We formally define the contraflow problem based on graph theory and provide a framework of computational workload to classify our approaches. A greedy heuristic is designed to produce high quality solutions with significant performance. A bottleneck relief heuristic is developed to deal with large numbers of evacuees. We evaluate the proposed approaches both analytically and experimentally using real world datasets. Experimental results show that our contraflow approaches can reduce evacuation time by 40% or more.     

多媒体通信中带度约束的多播路由算法

随着多媒体业务的发展,多播技术应用日益广泛,多播路由是要寻找连接源节点和一组目的节点的一棵多播树,这个问题在数学上归结为Steiner树问题,它是一个NPC问题。在实际网络中,网络节点具备不同的多播能力,有些节点不支持多播,有些节点支持多播,但为了保证网络速度和节点负载平衡,支持多播的节点要限制其复制信息的数量,即节点的多播能力受限。在这种情况下,寻找多播树变得更加困难,该文用节点的约束来表示敏个节点具备的多播能力,节点多播能力受限情况下的多播路由问题被称为带度约束的多播路由问题,其仍是一个NPC问题。该文提出了一种求解带度的约束多播路由问题的双层遗传算法。算法的基本思想是最优多播树应是一棵满足度约束的最小生成树,因此问题的关键在于如何找到包括在最优生成树中的Steiner节点。遗传算法 采用二进制编码方式,内层算法用于求解满足度约束的最小生成树;外层算法进行全局搜索。该文将算法在稀疏图上进行实验,为了更好地模拟真实网络,稀疏图中每个节点具有不同的多播能力,并且多播目的节点数目相比于网络节点数要小。实验对算法进行了三方面比较：（1）解的质量;（2）计算时间;（3）算法的收敛性。实验结果表明,文中提出的遗传算法能够找到费用较小的多播树,但是当网络规模增大时,算法的求解时间也较长。     

一种具有时延约束的组播路由算法研究*

对于多媒体应用等实时组播业务而言,组播路由算法不仅要考虑优化代价,还要考虑时延约束。针对这一问题,提出一种支持动态组播的时延受限低代价组播路由启发式算法(delay-constrained multicast algorithm,DCMA)。该算法基于DDMC算法进行扩展,采用新的指示函数和链路选择函数,综合考虑了时延和代价,有效保证了组播树的性能,而且时间复杂度低,可用于实际的应用系统中。     

Heuristic routing with bandwidth and energy constraints in sensor networks

Most of the routing algorithms devised for sensor networks considered either energy constraints or bandwidth constraints to maximize the network lifetime. In the real scenario, both energy and bandwidth are the scarcest resource for sensor networks. The energy constraints affect only sensor routing, whereas the link bandwidth affects both routing topology and data rate on each link. Therefore, a heuristic technique that combines both energy and bandwidth constraints for better routing in the wireless sensor networks is proposed. The link bandwidth is allocated based on the remaining energy making the routing solution feasible under bandwidth constraints. This scheme uses an energy efficient algorithm called nearest neighbor tree (NNT) for routing. The data gathered from the neighboring nodes are also aggregated based on averaging technique in order to reduce the number of data transmissions. Experimental results show that this technique yields good solutions to increase the sensor network lifetime. The proposed work is also tested for wildfire application.     

A methodology for multicriteria network partitioning

Conventional solution techniques are not appropriate for the multiobjective partitioning of large-scale distributed computer networks. The multiple (conflicting) goals and constraints include the assignment of all nodes without violating partition capacity limitations, maximal communication between nodes assigned to the same partition, minimal dispersion of technology classes, minimal diversity of technology classes within partitions, maximal reliability and minimal cost. This problem has been mathematically formulated and a two-stage, heuristic solution method was developed and programmed for solution and evaluation. The modelling and solution methodologies are flexible and may easily be applied to a wide range of network partitioning problems.     

Algorithms for multicast connection under multi-path routing model

Given a source node and a set of destination nodes in a network, multicast routing problem is usually treated as Steiner tree problem. Unlike this well-known tree based routing model, multicast routing under multi-path model is to find a set of paths rooted at the source node such that in each path at most a fixed number of destination nodes can be designated to receive the data and every destination node must be designated in a path to receive the data. The cost of routing is the total costs of paths found. In this paper we study how to construct a multicast routing of minimal cost under multi-path model. We propose two approximation algorithms for this NP-complete problem with guaranteed performance ratios.