This paper proposes two topology discovery algorithms for IP networks, namely, a network layer topology discovery algorithm and a link layer topology discovery algorithm. The network layer topology discovery algorithm discovers the subnets and devices in the network of interest and the connections among them. The devices in a subnet can be found by a network layer topology discovery algorithm; however, the connections among the devices cannot be obtained. The link layer topology discovery algorithm is proposed to find the devices in a subnet and the connections among them. The two algorithm are integrated to find the detailed topology map of an IP network. The proposed topology discovery algorithms are implemented based on the Tcl/Tk and Scotty environment. Some implementation details are discussed.

In the future asynchronous transfer mode (ATM) networks, an efficient virtual path (VP) control strategy must be applied to guarantee the network has high throughput with tolerable node processing load. The multistage VP control may be the best candidate since the tasks in this method are shared by the central node and local nodes, and it allows us to track the traffic changes while maintain a good state of the VP topology by reconfiguring it at regular or need based intervals. In this paper, we focus on the VP topology optimization problem in the multistage VP control. We first present the problem formulation in which the tradeoff between the network throughput and processing costs is considered, and then employ an algorithm based on a route-neuron Hopfield neural network (HNN) model to solve this problem. The numerical results demonstrate the HNN can converge to optimal solutions with high probability and stability while in other cases to near optimal solutions if the values of the system parameters in the route-neuron model are chosen according to some empirical formulas provided in this paper.

In this paper we consider a parallel and distributed computation of genetic algorithms on loosely-coupled multiprocessor systems. Loosely-coupled ones are more suitable for massively parallel processing and also more easily VLSI implementation than tightly-coupled ones. However, communication overhead on parallel processing is more serious for loosely-coupled ones. We propose in this paper a parallel and distributed execution method of genetic algorithm on loosely-coupled multiprocessor systems of fixed network topologies in which each processor element carries out genetic operations on its own chromosome set and communicates with only the neighbors in order to save communication overhead. We evaluate the proposed method on the multiprocessor systems with ring, torus, and hypercube topologies for benchmark problem instances. From the results, we find that the ring topology is more suitable for the proposed parallel and distributed execution since variety of chromosomes in the ring is kept much more than that in the others. Moreover, we also propose a new network topology called cone which is a hierarchical connection of ring topologies. We show its effectiveness by experimental evaluation.

This paper investigates the problem of constructing a logical multicasting tree which dispatches data to multiple destinations according to their bandwidth requirements. An optimization problem is formulated to minimize the maximum delay between a sender and multiple receivers. An algorithm of finding the optimum branching locations is presented. Performance analysis from the closed queueing network theory is given to evaluate a multicasting tree network based on this proposed algorithm.

This paper discusses the development of a design tool which supports a process for constructing PVC-based, ATM networks. Because of mathematical complexities, a heuristic approach has been adopted to find an optimal network configuration. Through a GUI, users define a physical network, and PVC networks which are logically constructed within the physical network. Based on the defined network configurations and user traffic demand, the tool evaluates performance measures. In response to the results of the evaluation, network designers can modify the network configuration to improve the performance. With the aid of this tool, they can repeat this interactive process until the estimated performance measures meet a desired quality. The tool has been applied to the design of several private ATM networks which will be constructed in the near future. The response time of this design tool is so fast that wait time can be negligible.

We present a topological framework of stepwise specification for concurrent systems in this paper. Some of description techniques can make topologies on the system space. Such topologies corresponds to abstract levels of those description techniques. Using a family of such description techniques, one can specify systems stepwisely. This framework allows to bridge various DTs and modularizing, so that global properties and module properties of systems become to be related to each other. Within this framework, we show derivation of a LOTOS cpecification from temporal logic formulae. An extended version of LOTOS with respect to concurrency is used in this paper. A semantics including concurrency is introduced to do this in this method. The method presented in this paper is applied to mobile telecommunication.

In this paper, we point out an architecture optimization problem for networks delivering services such as Video-On-Demand or, more precisely, two intertwined problems, i.e., the storage allocation of the videos among the storage nodes of the network and the choice of the network topology. We present and investigate the properties of a genetic algorithm which can handle such problems. This algorithm, as well as a greedy heuristics and simulated annealing, are then used to derive solutions in function of link and node cost parameters in a 36-node network. The results show that genetic algorithms are an effective class of algorithms for such problems, and possibly many other topology optimization problems.

The systematic treatment of speech-spectrum transformation can be obtained in terms of algebraic topology and Morse theory. Some properties of homotopy-equivalence in the transformation of 1- and 2-dimensional speech spectrum are discussed.

A modified deformable model is presented for constructing bijective topology preserving feature maps. The algorithm can solve the optimization problem in the input space as well as that in the output space. A saturating distance function alternative to the Euclid norm is employed to obtain compact space filling maps.

Management of control functions in large computer networks is a very difficult problem. One of the effective way to overcome the difficulty is to introduce hierarchical control structure (network cluster) in the management. When a fault occurred in the cluster, routing information at some nodes in the network must be updated in order to react the fault. However, the number of such nodes can be reduced by introducing ingenious topology into the cluster. This paper presents a fundamental discussion on network topology for a network cluster. First, L-FT is defined to represent a degree of fault-tolerance in a cluster with respect to link failures. Secondly, the minimum link problem M is defined to find the minimum number of links to make the cluster L-FT. The following results are obtained. (1) For a network cluster with the fault-tolerant topology 1-FT, at least 2n-2 links have to exist in the cluster where n is the number of border nodes in the cluster. (2) As far as connectivity of the whole network is held, for multiple L link failures in a L-FT cluster, the update of routing information at each node is localized within only the cluster containing the failed links. (3) Several hierarchical networks with fault-tolerant conditions are presented as case studies for a LAN and a MAN.

This paper is concerned with the continuous relation between models of the plant and the predicted performances of the system designed based on the models. To state the problem more precisely, let P be the transfer matrix of a plant model, and let A be the transfer matrix of interest of the designed system, which is regarded as a performance measure for evaluating the designed responses. A depends upon P and is written as A=A(P). From the practical point of view, it is necessary that the function A(P) should be continuous with respect to P. In this paper we consider the linear quadratic optimal servosystem with integrators (LQI) scheme as the design methodology, and prove that A(P) depends continuously on the plant transfer matrix P if the topology of the family of plants models is the graph topology. A numerical example is given for illustrating the result.

A network-topology-independent static task allocation strategy has been designed and implemented for massively parallel computers. For mapping a task graph to a processor graph, this strategy evaluates several functions that represent some intuitively feasible properties or the graphs. They include the connectivity with the allocated nodes, distance from the median of a graph, connectivity with candidate nodes, and the number of candidate nodes within a distance. Several greedy strategies are defined to guide the mapping process, utilizing the indicated function values. An allocation system has been designed and implemented based on the allocation strategy. In experiments we have defined about 1000 nodes in task graphs with regular and irregular topologies, and the same order of processors with mesh, tree, and hypercube topologies. The results are summarized as follows. 1) The system can yield 4.0 times better total communication costs than an arbitrary allocation. 2) It is difficult to select a single strategy capable of providing the best solutions for a wide range of task-processor combinations. 3) Comparison with hypercube-topology-dependent research indicates that our topology-independent allocator produces better results than the dependent ones. 4) The order of computaion time of the allocator is experimentally proved to be O (n2) where n represents the number of tasks.