Showing papers on "Network planning and design published in 1989"

Electricity Distribution Network Design

Abstract: Distribution networks represent a huge capital investment. To make sensible decisions about their investments, electricity utilities need to form clear-cut design policies and adopt the most accurate systemdesign procedures. Customers' expectations of the reliability of supply continue to rise, market pressures on the design engineer are growing stronger, and the increasing use of computers has changed the entire approach to distribution system design. Technical innovations have presented the design engineer with the means to improve system efficiency. Electricity Distribution Network Design was the first book to be entirely devoted to the planning and design of modern distribution systems, as apposed to the more general aspects of transmission and generation. This second edition has updated its treatment of computer-based planning and reliability. It also covers the implications of international standards, network information systems and distribution automation. With comprehensive and up-to-date bibliographies at the end of each chapter, the book will be useful both for students and for practising engineers involved in distribution network design.

A Dual-Ascent Procedure for Large-Scale Uncapacitated Network Design

Abstract: The fixed-charge network design problem arises in a variety of problem contexts including transportation, communication, and production scheduling. We develop a family of dual-ascent algorithms for this problem. This approach generalizes known ascent procedures for solving shortest path, plant location, Steiner network and directed spanning tree problems. Our computational results for several classes of test problems with up to 500 integer and 1.98 million continuous variables and constraints show that the dual-ascent procedure and an associated drop-add heuristic generate solutions that, in almost all cases, are guaranteed to be within 1 to 4% of optimality. Moreover, the procedure requires no more than 150 seconds on an IBM 3083 computer. The test problems correspond to dense and sparse networks, including some models that arise in freight transport.

An optimization approach for groundwater quality monitoring network design

Abstract: The optimal sampling plan for groundwater quality monitoring is formulated as a mixed integer programming (MIP) problem. A sampling plan consists of the number and locations of sampling sites as well as the temporal sampling frequency. The MIP network problem is defined by the minimization of the variance of estimation error subject to resource and unbiasedness constraints. The mean and covariance of the spatial/temporal variable (chloride concentration measurements) are derived from the advection-dispersion equation governing mass transport. The solution for the optimal sampling proceeds in two stages: (1) parameter estimation and (2) network optimization. The MIP model was successfully tested with a network design problem in a buried valley aquifer in Butler County, Ohio. The application illustrates the role of objective function, resource constraint, mass transport processes, and hydrogeologic setting in groundwater quality monitoring network design.

Design and implementation of an interactive optimization system for network design in the motor carrier industry

Abstract: We describe the design and implementation of an interactive optimization system for routing freight over a less-than-truckload motor carrier network. We formulate a very large, mixed integer programming problem, and develop a decomposition strategy based partly on the mathematical structure of the problem as well as a range of important, real-world issues and constraints. Then we develop and implement a local improvement heuristic in such a way as to keep the “man-in-the-loop,” using the analyst to make judgments regarding certain complex constraints and tradeoffs. Important aspects of the system include a range of modeling approximations to keep the problem tractable and the way the analyst evaluates the quality of the different numbers. The package was implemented and is currently being used on an ongoing basis by a major motor carrier. An overview of the major elements of the package is given as well as a summary of important implementation issues that arose during the three year project.

Hydrologic Uncertainty Measure and Network Design

Abstract: This paper presents a simple methodology, using the entropy concept, to estimate regional hydro logic uncertainty and information at both gaged and ungaged grids in a basin. The methodology described in this paper is applicable for (a) the selection of the optimum station from a dense network, using maximization of information transmission criteria, and (b) expansion of a network using data from an existing sparse network by means of the information interpolation concept and identification of the zones from minimum hydrologic information. The computation of single and joint entropy terms used in the above two cases depends upon single and multivariable probability density functions. In this paper, these terms are derived for the gamma distribution. The derived formulation for optimum hydrologic network design was tested using the data from a network of 29 rain gages on Sleeper River Experimental Watershed. For the purpose of network reduction, the watershed was divided into three subregions, and the optimum stations and their locations in each subregion were identified. To apply the network expansion methodology, only the network consisting of 13 stations was used, and feasible triangular elements were formed by joining the stations. Hydrologic information was calculated at various points on the line segments, and critical information zones were identified by plotting information contours. The entropy concept used in this paper, although derived for single and bivaviate gamma distribution, is general in type and can easily be modified for other distributions by a simple variable transformation criterion.

Fiberoptic circuit network design under reliability constraints

Abstract: A general mathematical model for a network design problem with reliability constraints and a revised formulation which seems particularly appropriate for fiber-optics networks is presented. Upper and lower bounding procedures based on continuous relaxations of this modified formulation are described. Preliminary computational results are reported. Limited computational results indicate a good performance of the algorithm, producing a gap between lower and upper bounds that is sufficiently small for a branch-and-bound procedure to be applicable. >

Analysis of a flow problem with fixed charges

Abstract: This article addresses a problem that comes up frequently in network design, and routing. A source is to distribute flows to nodes in the network. Sending flow along an arc involves a fixed cost for using the arc and a variable cost for each ujnit of flow. We show tht the problem of finding a minimum cost collection of arcs along which flows will be directed is an NP-hard problem. We describe a procedure of solving the problem to optimality and several heuristics. In particular, we conclude that the use of polynomially derived Lagrange multipliers yields good quality solutions and bounds and can be implemented in a distributed processing mode in the network.

ATM communications network control by neural network

Abstract: A learning control method using neural networks for service quality control in the asynchronous transfer mode (ATM) network is described. An ATM network is a high-speed packet-switching network for the data transmission layer of B-ISDN (broadband integrated services digital network) which provides multimedia services, including voice, data and video. Service quality control is one of the most crucial issues in realizing a flexible ATM network. It is a challenging research task to build an efficient network controller that can control the network traffic even when the precise characteristics of the source traffic are not known and the service quality requirements change over time. The proposed ATM network controller is flexible in function and simple in implementation because neural networks using backpropagation learn the relations between the offered traffic and service qualities. A training data selection method called leaky pattern tables is proposed for learning the accurate relations. The performance of the proposed controller is evaluated by simulation of a basic call regulation model. >

Using Local Models to Control Movement

Abstract: This paper explores the use of a model neural network for motor learning. Steinbuch and Taylor presented neural network designs to do nearest neighbor lookup in the early 1960s. In this paper their nearest neighbor network is augmented with a local model network, which fits a local model to a set of nearest neighbors. The network design is equivalent to local regression. This network architecture can represent smooth nonlinear functions, yet has simple training rules with a single global optimum. The network has been used for motor learning of a simulated arm and a simulated running machine.

Blocking evaluation for networks with residual capacity adaptive routing

Abstract: An algorithm is proposed for obtaining conservative estimates for the end-to-end blocking probability of networks operating with residual capacity adaptive routing. Two important requirements are that it should be fast enough for use within an iterative network design procedure and have an accuracy sufficient for that purpose. The algorithm is based on the assumption that the stationary behavior of residual capacity adaptive routing can be adequately modeled by a nonadaptive routing with suitably chosen parameters. An algorithm is proposed for the stationary version that is stable and fast but overestimates the blocking. A number of modifications of the model to improve its accuracy are examined. It is concluded that the model can be used for network design if a conservative solution is acceptable. >

Structured systems analysis methodology for design of an ATM network architecture

Abstract: The asynchronous transfer mode (ATM) network design problem is treated as a resource-allocation problem. Traffic control is applied to different entities: packets, bursts, calls, and flows. Each of these entities can be controlled locally, within an exchange, or globally, at the network level. This gives rise to a multistrata architecture, where the resource-allocation stratum is defined both by the layer of traffic flow and the control level. Dedicated and virtual connections can be set up in all strata: for bursts, calls, subscriptions, and flows, at the exchange, subnetwork, and network levels. The open systems interconnection protocols are used to map heterogeneous user entities onto uniform network entities. The critical load is defined, which is where burst and call fluctuations begin to result in long queues and big packet delays. The critical load is used to determine thresholds, at the network and exchange level, for the number of virtual or dedicated connections which can be established in each traffic class. >

Robust design and planning of a worldwide intelligent network

Abstract: The authors describe the structure of the worldwide intelligent network (WIN), describe methods for its design and planning, investigate the adequacy of decentralized control for problem-free worldwide call completion, explore the feasibility of adaptive routing and control concepts, discuss network robustness/reliability objectives, and describe a strategy for achieving these objectives for all cooperating international carriers. Several decentralized adaptive routing policies that are particularly attractive in the WIN environment and network performance improvements that can be achieved with the introduction of flexible routing capabilities are characterized. It is shown by example that network integration coupled with flexible routing and bandwidth allocation for preferential treatment of new services provides an effective approach for robust and economical new service provisioning. >

The cascade analysis for energy and process integration of batch processes. II: Network design and process scheduling

Abstract: In the first paper the use of the Cascade analysis to obtain energy targets for batch processes was described. This paper shows how these targets may be applied to process design and revamping

A network environment for studying multimedia network architecture and control

Abstract: In Bellcore's Integrated Media Architecture Laboratory (IMAL) architecture, control, and network design issues (including performance and its implications, traffic engineering, resource sizing, operations, and network architectures) of network-based multimedia services that are likely to exist in future broadband networks (e.g. broadband integrated services digital network) are studied. The authors present an overview of multimedia services that use audio, video, graphics, text, and other sorts of data; describe the laboratory environment used to support these services; and provide a high-level description of how these services have been implemented as networked modules. It is noted that, not only must these applications to able to exist on the same network, but they should be able to coordinate their functions and share information in the most natural format. The development of generic server models for all of these services and efforts to make their use intuitive are discussed. >

A CMOS neural network for pattern association

Abstract: The authors present an analog complementary metal-oxide semiconductor (CMOS) version of a model for pattern association, along with discussions of design philosophy, electrical results, and a chip architecture for a 512-element, feed-forward IC. They discuss hardware implementations of neural networks and the effect of limited interconnections. They then examine network design, processor-element design, and system operation. >

Enhanced network survivability through balanced resource criticality

Abstract: The authors describe two entropy-based measures that can be used to assess how close a network design comes to being maximally survivable: normalized node entropy (NNE) and normalized link entropy (NLE). Maximum survivability is achieved when the enemy cannot identify critical points of failure and must remove a maximum number of nodes/links before the network becomes disconnected. The normalized node and link entropy measures provide the network designer with an indication of how well individual network resources have been used to produce a highly survivable network structure. For instance, an NNE value of unity occurs in network configurations where all nodes appear equally important to the interconnection structure, such as in a ring or a fully connected network. In contrast, star configurations have NNE values of zero, since the center node can be identified as most critical to maintaining the network's interconnection structure. >

Transportation-network design problem: application of a hierarchical search algorithm

Abstract: Two variants of a network design problem are solved by application of the tree search method. The first formulation aims to reduce a specified vehicle-minutes of traffic congestion at the least possible budget expenditure, and the second minimizes traffic congestion for a given budget. Both involve system-optimizing traffic assignment models with multipath flows. The solution method consists of network abstraction, tree search, and network disaggregation--collectively referred to as the "hierarchical search algorithm." It is shown that such an algorithm reduces the search space by reducing the number of nodes and links and providing a tighter bound during the tree search. It also groups detailed links according to the function they perform--whether it be access/egress, line-haul, bypass, or internal circulation. However, the algorithm yields only a suboptimal solution, the quality of which is measured by an error function. The metropolitan network of Taipei, Taiwan, Republic of China, is used as a case study to verify some of the algorithmic properties, confirming its role in real-world applications. Finally, the performance of the algorithm, which is based on network abstraction, is favorably compared with a network-extraction network-design model.

Dynamic program modification in telecommunications systems

Abstract: In today's public telecommunications network, the logic of telecommunications services is typically defined in software that executes in stored program control switching systems or other network elements. Changes in network functionality require that new versions of software be installed in these network elements, a process that has proven inconvenient and error-prone. The authors expect that changes to network software will occur with increasing frequency in the future, exacerbating the software update problem. They discuss the requirements for performing software updates in the telecommunications network and describe a specific approach that allows dynamic modification of programs running in a distributed environment. They also discuss the implications of this approach for the design of telecommunications software.

A rule-based system for packet radio network design

Abstract: A general method is introduced that is capable of improving network capacity by altering connectivity values and can be used on a wide range of packet radio network topologies, traffic requirements, and protocols. The approach uses artificial intelligence techniques to formulate design rules which quantitatively describe individual aspects of the capacity/connectivity dependence. Incorporation of the design rules into a rule-based computer optimization program produces, on average, 15-25% capacity improvement for both random and regular network inputs. Optimization results lead to conclusions about efficient network topology and operation, and permit further capacity/connectivity generalizations. The approach used, as well as many of the rules developed, go beyond the domain of packet radio networks, and are applicable to many general network design problems. >

Applications of artificial intelligence for meeting network management challenges in the 1990s

Abstract: The authors describe the prototype application of selected techniques from artificial intelligence to selected network management problems. One software prototype supports tactical planning activities using knowledge-based system techniques. A second software prototype applies heuristic search techniques to a network design problem. The authors discuss possible applications of neural network techniques to switch message diagnosis. >

SIGnet: a new ultra-high-speed lightwave network architecture

Abstract: A high-speed network architecture, SIGnet (Slotted Interconnected-Grid network), is introduced. SIGnet is intended for metropolitan and extended-metropolitan areas and is currently being studied under the extremely high-speed networks project of the Telecommunications Research Institute of Ontario. In SIGnet, the topology is piecewise-regular and permits bandwidth allocation and network evolution which is much more easily accomplished than in previous designs. Since a system consisting of an arbitrary piecewise interconnection of regular topological segments can be engineered, many of the problems are alleviated. An introduction to the new network design is given, and some preliminary results obtained concerning the traffic processing schemes which have been investigated are presented. >

A collective computation approach to automatic target recognition

Abstract: A neural network associative memory is used to guide the template-matching process in a digital simulation model of a third-generation fuse. The templates are produced by analytic models of target interaction with several simultaneous sensors and are stored by means of the Hinton-Sejnowski formula in a symmetrically cross-coupled (Hopfield) network. A description is given of some salient features of network design and simulation. The performance gain that can be achieved with this collective computation approach is limited mainly by the size of the network. >

Asymptotic performance analysis of hybrid ARQ protocols in slotted direct-sequence code division multiple-access networks

Abstract: The performance of hybrid automatic repeat-request (ARQ) protocols in slotted direct-sequence code-division multiple-access networks is analyzed. A Markov model is used to derive throughput-delay expressions in terms of the channel cutoff rate and capacity. Network design parameters are identified and their dependency on systems parameters is examined in detail. It is shown that, for a given population size, traffic intensity, and ratio of bit energy to background noise, there is an optimal probability of retransmission, code rate, and processing gain that maximizes performance. The stability of the network is also discussed. >

Solving large telecommunications network loading problems

Abstract: Telecommunications network loading problems focus on routing traffic through networks so as to satisfy the demand forecast between all pairs of nodes. The objective is to minimize the total routing costs subject to satisfying capacity constraints associated with the individual links. This paper presents a nonlinear programming formulation for the multiperiod network loading problem, a problem that appears in many guises throughout network planning. Such problems are also known in the operations research literature as (multiperiod) multicommodity network flow problems. The resulting optimization problem has a very large number of variables and constraints. We describe the implementation of a nonlinear optimization algorithm, the Frank-Wolfe method with PARTAN extension and projective gradient acceleration, on a parallel vector processor for solving these large dynamic network loading problems. Our computational experience shows that our algorithm solves large, realistic loading problems very efficiently and is serving as a valuable tool for telecommunications network planning.

Performance evaluation of adaptive traffic routing in a metropolitan network: a case study

Abstract: A performance analysis of adaptive traffic in the telephone network of Marseilles, France is presented. The authors give the main reasons for introducing flexible routing-especially, state-dependent routing-in modern telephone networks. They present the Marseilles network under study and briefly describe the routing algorithm and the network design method used. They consider a number of scenarios ranging from traffic overloads to network failures in order to evaluate the robustness and performance of the adaptively routed network. Simulations that emphasize the role of state-dependent routing in network efficiency are presented and analyzed. In some specific cases, the state-dependent routing is complemented with predictive control actions to limit low priority or overflow traffic. This results in an improved grade of service. It is concluded that adaptive traffic routing can cope with a large range of network conditions, such as traffic overloads and equipment failures. >