A post-optimization method for the routing and wavelength assignment problem applied to scheduled lightpath demands

We consider here a NP-hard problem related to the Routing and Wavelength Assignment (RWA) problem in optical networks, dealing with Scheduled Lightpath Demands (SLDs). An SLD is a connection demand between two nodes of the network, during a certain time. Given a set of SLDs, we want to assign a lightpath, i.e. a routing path and a wavelength, to each SLD, so that the total number of required wavelengths is minimized. The constraints are the following: a same wavelength must be assigned all along the edges of the routing path of any SLD; at any time, a given wavelength on a given edge of the network cannot be used to satisfy more than one SLD. To solve this problem, we design a post-optimization method improving the solutions provided by a heuristic. The experimental results show that this post-optimization method is quite efficient to reduce the number of necessary wavelengths.     

A preferential attachment model with Poisson growth for scale-free networks

We propose a scale-free network model with a tunable power-law exponent. The Poisson growth model, as we call it, is an offshoot of the celebrated model of Barabási and Albert where a network is generated iteratively from a small seed network; at each step a node is added together with a number of incident edges preferentially attached to nodes already in the network. A key feature of our model is that the number of edges added at each step is a random variable with Poisson distribution, and, unlike the Barabási–Albert model where this quantity is fixed, it can generate any network. Our model is motivated by an application in Bayesian inference implemented as Markov chain Monte Carlo to estimate a network; for this purpose, we also give a formula for the probability of a network under our model.     

The pairwise flowtime network construction problem

It is required to find an optimal order of constructing the edges of a network so as to minimize the sum of the weighted connection times of relevant pairs of vertices. Construction can be performed anytime anywhere in the network, with a fixed overall construction speed. The problem is strongly NP-hard even on stars. We present polynomial algorithms for the problem on trees with a fixed number of leaves, and on general networks with a fixed number of relevant pairs.     

A dynamic edge covering and scheduling problem: complexity results and approximation algorithms

We consider a new dynamic edge covering and scheduling problem that focuses on assigning resources to nodes in a network to minimize the amount of time required to process all edges in it. Resources need to be co-located at the endpoints of an edge for it to be processed and, therefore, this problem contains both edge covering and scheduling decisions. These new problems have motivating applications in traffic systems and military intelligence operations. We provide complexity results for the dynamic edge covering and scheduling problem over different types of networks. We then show that existing approximation algorithms for parallel machine scheduling problems can be leveraged to provide approximation algorithms for this new class of problems over certain types of networks.     

Parameter Identification Based on First Order Approximation Neural Networks

Constitutive models for structural analyses contain material parameters. Usually not all of them can be determined a priori with sufficient accuracy. They must be set such that numerical results agree with available measurements as well as possible. Hence, an inverse problem must be solved. In order to keep the number of the required numerical calculations for parameter identification as small as possible, back analyses are performed iteratively. In each iteration step, a backpropagation artificial neural network (BPANN) is trained to approximate results of already performed numerical analyses. In this paper the classical zero‐order training algorithm is extended in order to obtain first‐order approximation neural networks. Based on the trained BPANN, a prognosis of optimal parameters can be obtained.     

Vulnerability of complex networks

We consider normalized average edge betweenness of a network as a metric of network vulnerability. We suggest that normalized average edge betweenness together with is relative difference when certain number of nodes and/or edges are removed from the network is a measure of network vulnerability, called vulnerability index. Vulnerability index is calculated for four synthetic networks: Erdős–Rényi (ER) random networks, Barabási–Albert (BA) model of scale-free networks, Watts–Strogatz (WS) model of small-world networks, and geometric random networks. Real-world networks for which vulnerability index is calculated include: two human brain networks, three urban networks, one collaboration network, and two power grid networks. We find that WS model of small-world networks and biological networks (human brain networks) are the most robust networks among all networks studied in the paper.     

The green function of the boundary-value problem on a star-shaped graph

We consider a planar graph consisting of three edges with one common vertex. We are interested in the sign of the Green function of the boundary-value problem for a fourth-order equation. This problem models deformations of star-shaped coupled networks of beams. We assume that the network is fixed at each vertex, and all beams are rigidly jointed at their common vertex. We prove that the Green function is positive on diagonal squares and establish a sufficient condition for its positivity inside its definition domain.     

几种特殊结构全光网中多播路由的波长分配算法

研究全光WDM网络中多播请求的路由与波长分配问题.给定网络拓扑和一组多播通信请求,要求对其进行路由和波长分配,满足波长连续性和波长无冲突约束,使得所用的波长总数最少.就几类特殊网络进行了研究.首先对二分树网络进行了研究,此时问题是多项式时间可求解的.其次对树网络进行了讨论,证明了即使是星网络,问题也不存在近似比小于m1/2-ρ(0＜ρ＜1))的近似算法,除非NP=ZPP,这里m是星图的边数.随后给出了近似比为(√m 1)(log r/√m 1 1)的近似算法,此结果对一般图也成立.最后考虑了环网和树环网,给出了近似比为3.6和2△的近似算法,这里△是图的最大度.     

Neural and delay based heuristics for the Steiner problem in networks

High speed networks such as the B-ISDN must be adequately equipped to handle multipoint communication in a fast and economical manner. Multicast applications include desktop video conferencing, distance learning, distributed database applications, etc. In networks employing the asynchronous transfer mode (ATM) technology, routing a multicast is achieved by constructing a tree that spans the source and all the destinations. For the purpose of routing, the network is modeled as a weighted, undirected graph. The graph-theoretic solution is to find a minimum Steiner tree for the graph given a set of destinations. This formulation suffices for building multicast trees with a single optimization constraint as would be the xcase for best effort transport. For real-time traffic, however, it is necessary to ensure that the delay between the sender and each of the receivers is bounded. In this case the network is modeled as an undirected graph, where the edges have both a cost and a delay associated with them. The graph-theoretic solution is then to find a constrained minimum Steiner tree such that the delay between the source and each of the destinations does not violate the specified bound. Both of these problems are NP-complete. In this paper we review prior work on the multipoint routing problem and discuss the formulation of the unconstrained and constrained Steiner problems. We use the random neural network (RNN) to significantly improve the quality of trees found by the two existing best heuristics for finding Steiner trees - the minimum spanning tree heuristic and the average distance heuristic. We also develop a new heuristic for finding delay constrained Steiner trees. Experimental results are presented which show that the new heuristics improve significantly over existing ones.     

完全κ叉树的离散数和完整度

图的离散数和完整度是比较理想的刻画网络抗毁性的度量参数,而完全k叉树作为重要的网络结构被广泛地应用在通信网和嵌入式系统芯片的优化设计方面.通过界定了完全k叉树的离散数和完整度,从某种程度刻画了网络的抗毁性,为网络设计提供理论依据,同时修正了相关文献的错误.     

Jamming communication networks under complete uncertainty

This paper describes a problem of interdicting/jamming wireless communication networks in uncertain environments. Jamming communication networks is an important problem with many applications, but has received relatively little attention in the literature. Most of the work on network interdiction is focused on preventing jamming and analyzing network vulnerabilities. Here, we consider the case where there is no information about the network to be jammed. Thus, the problem is reduced to jamming all points in the area of interest. The optimal solution will determine the locations of the minimum number of jamming devices required to suppress the network. We consider a subproblem which places jamming devices on the nodes of a uniform grid over the area of interest. The objective here is to determine the maximum grid step size. We derive upper and lower bounds for this problem and provide a convergence result. Further, we prove that due to the cumulative effect of the jamming devices, the proposed method produces better solutions than the classical technique of covering the region with uniform circles.     

Partitioning (hierarchically clustered) complex networks via size-constrained graph clustering

The most commonly used method to tackle the graph partitioning problem in practice is the multilevel metaheuristic. In this paper we introduce size-constrained label propagation (SCLaP) and show how it can be used to instantiate both the coarsening phase and the refinement phase of multilevel graph partitioning. We mainly target networks with highly irregular and hierarchically clustered structure (but other network types can be partitioned as well). Additionally, we augment the basic algorithm with several extensions to further improve its speed and/or solution quality. Depending on the configuration of the resulting partitioner using SCLaP, we are able to compute high-quality partitions outperforming all competitors, or instead, to compute similarly good partitions as the best competitor in terms of quality, hMetis, while being an order of magnitude faster. Our fastest configuration partitions the largest real-world graph in our study (it has 3.3 billion edges) with sequential code in about ten minutes while cutting less than half of the edges than the fastest competitor, kMetis.     

Cycle embedding in star graphs with more conditional faulty edges

The star graph is one of the most attractive interconnection networks. The cycle embedding problem is widely discussed in many networks, and edge fault tolerance is an important issue for networks since edge failures may occur when a network is put into use. In this paper, we investigate the cycle embedding problem in star graphs with conditional faulty edges. We show that there exist fault-free cycles of all even lengths from 6 to n! in any n-dimensional star graph S_n (n ? 4) with ?3n − 10 faulty edges in which each node is incident with at least two fault-free edges. Our result not only improves the previously best known result where the number of tolerable faulty edges is up to 2n − 7, but also extends the result that there exists a fault-free Hamiltonian cycle under the same condition.     

Network design problem with relays: A genetic algorithm with a path-based crossover and a set covering formulation

The network design problem with relays arises in telecommunications and distribution systems where the payload must be reprocessed at intermediate stations called relays on the route from its origin to its destination. In fiber-optic networks, for example, optical signals may be regenerated several times to overcome signal degradation because of attenuation and other factors. Given a network and a set of commodities, the network design problem with relays involves selecting network edges, determining a route for each commodity, and locating relays to minimize the network design cost. This paper presents a new formulation to the problem based on set covering constraints. The new formulation is used to design a genetic algorithm with a specialized crossover/mutation operator which generates a feasible path for each commodity, and the locations of relays on these paths are determined by solving the corresponding set covering problem. Computational experiments show that the proposed approach can outperform other approaches, particularly on large size problems.     

Minisum location of a travelling salesman on simple networks

In this paper, we study the travelling salesman location problem on simple networks. The problem is to find the optimal home location of the salesman (e.g., a repair unit) that in each working day, must visit all the customers that require service. The number of customers as well as their location can change from day to day. In simple networks, each link belongs to at most one cycle. The paper includes O(n) algorithms for several types of simple networks and thus, avoids the calculation of 2ⁿ − 1 probabilities for each possible tour that may occur (customers are located at n nodesof the network).     

移位交换网的最优路由算法

移位交换网是重要的互联网络之一 ,在并行计算中有着广泛应用 .然而 ,它缺少任意点对间的最短路由算法 .已有的路由算法都不能保证其任意节点对间都是最短路由 .文中给出了一个最短路由算法 ,也是最优路由算法 ,它使得从源节点到目的节点的任何信息都是沿最短路由传输 .同时 ,我们还得到了任意节点对间的距离公式     

Two-Connected Networks with Rings of Bounded Cardinality

We study the problem of designing at minimum cost a two-connected network such that each edge belongs to a cycle using at most K edges. This problem is a particular case of the two-connected networks with bounded meshes problem studied by Fortz, Labbé and Maffioli (Operations Research, vol. 48, no. 6, pp. 866–877, 2000).In this paper, we compute a lower bound on the number of edges in a feasible solution, we show that the problem is strongly NP-complete for any fixed K, and we derive a new class of facet defining inequalities. Numerical results obtained with a branch-and-cut algorithm using these inequalities show their effectiveness for solving the problem.     

Optimal egress time calculation and path generation for large evacuation networks

Finding the optimal clearance time and deciding the path and schedule of evacuation for large networks have traditionally been computationally intensive. In this paper, we propose a new method for finding the solution for this dynamic network flow problem with considerably lower computation time. Using a three phase solution method, we provide solutions for required clearance time for complete evacuation, minimum number of evacuation paths required for evacuation in least possible time and the starting schedules on those paths. First, a lower bound on the clearance time is calculated using minimum cost dynamic network flow model on a modified network graph representing the transportation network. Next, a solution pool of feasible paths between all O-D pairs is generated. Using the input from the first two models, a flow assignment model is developed to select the best paths from the pool and assign flow and decide schedule for evacuation with lowest clearance time possible. All the proposed models are mixed integer linear programing models and formulation is done for System Optimum (SO) scenario where the emphasis is on complete network evacuation in minimum possible clearance time without any preset priority. We demonstrate that the model can handle large size networks with low computation time. A numerical example illustrates the applicability and effectiveness of the proposed approach for evacuation.     

An Alternative Model for Queueing Systems with Single Arrivals,Batch Services and Customer Coalescence

In this paper we consider a queueing system with single arrivals, batch services and customer coalescence and we use it as a building block for constructing queueing networks that incorporate such characteristics. Chao et al. (1996) considered a similar model and they proved that it possesses a geometric product form stationary distribution, under the assumption that if the number of units present at a service completion epoch is less than the required number of units, then all the units coalesce into an incomplete (defective) batch which leaves the system. We drop this assumption and we study a model without incomplete batches. We prove that the stationary distribution of such a queue has a nearly geometric form. Using quasi-reversibility arguments we construct a network model with such queues which provides relevant bounds and approximations for the behaviour of assembly processes. Several issues about the validity of these bounds and approximations are also discussed.     

Coupled cell networks: minimality

Non-isomorphic coupled cell networks with the same number of cells and with equivalent dynamics are said to be ODE-equivalent. Moreover, they are all related by a linear algebra condition involving their graph adjacency matrices. A network in an ODE-class is said to be minimal if it has a minimum number of edges among all the networks of the class. In this short paper we review the characterization of the minimal networks of an ODE-equivalence class and we present an example for the case of non-homogeneous networks. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)