Design Of Computer Networks Research Articles

Tradeoff decisions in the design of a backbone computer network using visualization

Visualization provides a useful tool for analyzing large, complex data sets. In the design of backbone computer networks, rough-cut design decisions can gain from a visual analysis of the generated solution with respect to design parameters such as average message delay, delay cost, average message length and total network operating costs. In this paper, we show how two-dimensional and three-dimensional surface and glyph representations can be used for understanding the cost–delay tradeoffs involved in the network design problem, and an idea of the ‘efficient frontier’ where the user may choose to operate. It provides an opportunity to revisit relationships that exist between the different network design parameters as well as discover new ones.

The Development of Localized Algorithms in Wireless Sensor Networks

Advances in sensor technology and wireless communications have made networked microsensors possible, where each sensor individually senses the environment but collaboratively achieves complex information gathering and dissemination tasks. These networked sensors, however, possess several characteristics that have challenged many aspects of traditional computer network design, such as the scalability issue caused by the sheer amount of sensor nodes, the infrastructureless network, and the stringent resource onboard the sensors. These new features call for a re-design of overall structure of applications and services. It has been widely accepted that practical localized algorithms is probably the best solution to wireless sensor networks. In this article, we discuss recent research results on localized algorithms design in supporting services and applications in sensor networks.

Community Technology and Democratic Rationalization

The objective of this paper is to explore questions of human agency and democratic process in the technical sphere through the example of "virtual community." The formation of relatively stable long-term group associations--community in the broad sense of the term--is the scene on which a large share of human development occurs. As such it is a fundamental human value mobilizing diverse ideologies and sensitivities. The promise of realizing this value in a new domain naturally stirs up much excitement among optimistic observers of the Internet. At the same time, the eagerness to place hopes for community in a technical system flies in the face of an influential intellectual tradition of technology criticism. This eagerness seems even more naive in the light of the recent commercialization of so much Internet activity. Despite the widespread skepticism, we believe the growth of virtual community is significant for an inquiry into the democratization of technology.We show that conflicting answers to the central question of the present theoretical debate--Is community possible on computer networks?--generalize from particular features of systems and software prevalent at different stages in the development of computer networking. We conclude that research should focus instead on how to design computer networks to better support community activities and values.

Estimation of all-terminal network reliability using an artificial neural network

The exact calculation of all-terminal network reliability is an NP-hard problem, with computational effort growing exponentially with the number of nodes and links in the network. During optimal network design, a huge number of candidate topologies are typically examined with each requiring a network reliability calculation. Because of the impracticality of calculating all-terminal network reliability for networks of moderate to large size, Monte Carlo simulation methods to estimate network reliability and upper and lower bounds to bound reliability have been used as alternatives. This paper puts forth another alternative to the estimation of all-terminal network reliability — that of artificial neural network (ANN) predictive models. Neural networks are constructed, trained and validated using the network topologies, the link reliabilities, and a network reliability upperbound as inputs and the exact network reliability as the target. A hierarchical approach is used: a general neural network screens all network topologies for reliability followed by a specialized neural network for highly reliable network designs. Both networks with identical link reliability and networks with varying link reliability are studied. Results, using a grouped cross-validation approach, show that the ANN approach yields more precise estimates than the upperbound, especially in the worst cases. Using the reliability estimation methods of the ANN, the upperbound and backtracking, optimal network design by simulated annealing is considered. Results show that the ANN regularly produces superior network designs at a reasonable computational cost. Scope and purpose An important application area of operations research is the design of structures, products or systems where both technical and business aspects must be considered. One expanding design domain is the design of computer or communications networks. While cost is a prime consideration, reliability is equally important. A common reliability measure is all-terminal reliability, the probability that all nodes (computers or terminals) on the network can communicate with all others. Exact calculation of all-terminal reliability is an NP-hard problem, precluding its use during optimal network topology design, where this calculation must be made thousands or millions of times. This paper presents a novel computationally practical method for estimating all-terminal network reliability. Is shown how a neural network can be used to estimate all-terminal network reliability by using the network topology, the link reliabilities and an upperbound on all-terminal network reliability as inputs. The neural network is trained and validated on a very minute fraction of possible network topologies, and once trained, it can be used without restriction during network design for a topology of a fixed number of nodes. The trained neural network is extremely fast computationally and can accommodate a variety of network design problems. The neural network approach, an upper bound approach and an exact backtracking calculation are compared for network design using simulated annealing for optimization and show that the neural network approach yields superior designs at manageable computational cost.

Optimization of an internationally distributed air–ground airline telecommunication system

This paper presents the problem of optimally dimensioning a new geographically distributed computer system that handles all communications between aircraft and airline operation centers. Since computers are distributed on three continents, the service demand per site (as measured by messages to be treated) can vary greatly with the time of day. The model optimizes costs while taking advantage of the variation of demand over time and the sharing of load among the sites. The model is a mixed integer program with non-linear constraints. An algorithm is proposed to solve the problem to optimality. Test data provided by SITA were used to evaluate the quality of the solution. Scope and purpose The scope of this paper is to show how operations research modelling and resolution techniques can be used to solve to optimality a unique computer network design application. The paper presents the application, a novel modelling approach and shows how to use the particular constraints of the system to yield to the optimal solution despite the problem complexity. Given the emergence of e-commerce and International Application Service Providers (ASPs), this type of internationally distributed network design problem will become quite common in the near future.

Gateways—just as important as standards: How the internet won the “religious war” over standards in Scandinavia

This article concerns the Nordunet project and its “plug.” It is a history about how the Internet “won” the “religious war” about computer communication protocol standards in Scandinavia. It teaches us important lessons about how the Nordic countries (except Denmark) became the leading ones in the adoption and use of the Internet. On a more general level this story also teaches us an important lesson about the importance of gateways in the design and establishment of large scale computer networks and information infrastructures. It is a universal truth that the development of such technologies requires standards. And that gateways are equally important. The main conclusion drawn is that what matters in the development of such technologies is to combine and balance the use of gateways and standards in a proper way.

A dynamic tabu search for large-scale generalised assignment problems

A new tabu search (TS) for application to very large-scale generalised assignment and other combinatorial optimisation problems is presented in this paper. The new TS applies dynamic oscillation of feasible verses infeasible search and neighbourhood sample sizes that vary throughout the solution process. The dynamic oscillation and neighbourhood sample sizes are controlled by the success of the search as the solution progresses, to allow a faster increase in solution quality per unit time. Application of the TS to three types of randomly generated very large-scale generalised assignment problem instances was performed for sizes of up to 50 000 jobs and 40 agents. The new TS gave superior solutions to existing versions on all nearly occasions, given a fixed CPU time. For a fixed solution quality, the best of the existing versions required 1.5–3 times as much CPU time. Scope and purpose Very large-scale generalised assignment problems of several thousand jobs have important real-life applications such as vehicle routing, project planning, computer network design and sugar cane supply management. Existing heuristic techniques for the NP-hard problem are designed for medium-size problem instances of a few 100 jobs, since CPU time or search space significantly increases with problem size. This paper puts forward a new version of tabu search designed for very large generalised assignment and other large combinatorial optimisation problems. The new tabu search incorporates dynamic oscillation and neighbourhood sample sizes. These are controlled by the success of the search as the solution progresses, to allow a faster increase in solution quality per unit time. The results reported in the paper for problem sizes of up to 50 000 jobs and 40 agents, show a considerable reduction in CPU time over existing versions of tabu search to reach a desired solution quality.

Computer networks design using hybrid fuzzy expert systems

Designing and configuring large computer networks to support a variety of applications and computational environments is difficult, as it not only requires highly specialized technical skills and knowledge, but also a deep understanding of a dynamic commercial market. Hybrid fuzzy expert systems integrate fuzzy expert systems and neural networks methods replacing classical hard decision methods and providing better performance than traditional techniques. In this paper, we present an integrated fuzzy expert system, machine learning, and neural networks approach to large structured computer networks design and evaluation. After presenting an overview of the system and the major research choices, we describe in detail the system's modules and present examples of its potential use.

Preface: Volume 43

Formal Methods ElsewhereA Satellite Workshop of FORTE-PSTV-2000 devoted to applications of formal methods to areas other than communication protocols and software engineeringA wide variety of formal models, languages and methods have been developed in the last two decades for supporting the specification, design, verification, implementation and testing of computer networks and distributed software systems. These include CCS, pi-calculus, timed and stochastic process algebra, VDM, Z, B, Automata and Timed Automata, Petri Nets, Statecharts, Logics, TLA, Message Sequence Charts, ADT's, OBJ, Larch, formal Object-Oriented approaches, the international standards Estelle, LOTOS, SDL, ASN.1 and TTCN, and others.Formal specification languages have been designed to support the description of system structure and behaviour in terms of concepts such as event occurrence, observation and experiment, temporal ordering, causality, cooperation and synchronisation among entities, non determinism, concurrency and parallelism, state changes and invariants, and others. While considerable experience has been gained in the application of formal methods to the areas for which they were initially conceived, the high abstraction level of these concepts suggests that they could play an important role in several other disciplines such as chemistry, biology, physics and even arts, humanites and social sciences.After two decades of ‘traditional’ applications, during which the initial gap between the excessive optimism of academic supporters and the skepticism of industrial detractors have been substantially reduced, often leading to a positive and constructive attitude towards their adoption, formal methods are perhaps ready to spread out of their native territory and, at the turn of the decade and millenium, invade new exciting areas of research, thus providing a much wider exploitation of the huge intellectual investment behind their definition. In fact, it is often the case that a technique designed with a particular application in mind, turns out to perform better and to be more useful in a context other than the originally intended one.For more information on the spectrum of topics within the remit of the FM-Elsewhere initiative, see this web page. A list of existing “Elsewhere” applications of formal methods can also be accessed at this web page.The FM-Elsewhere workshop, co-located with FORTE-PSTV-2000 in Pisa, was a forum for researchers interested in the application of formal methods, as identified above, to virtually any area of research, except communication protocols and software engineering. The talks included in the workshop covered the spectrum of FM-Elsewhere areas. In particular, applications of formal methods to all the following areas were considered, safety analysis of cockpit interfaces;solving games and puzzles using state space exploration techniques;modelling theories of the mind;usability anaylsis of human computer interfaces;formal definition of linguistic systems; andmodelling in mechanics and physics.Thanks should be made to a number of people. Firstly, FM-Elsewhere 2000 was fortunate to have two celebrated invited speakers, John Rushby who spoke on how model checking techniques can be used in analysing cockpit interfaces; andProfessor David Duce who spoke on using state based specification techniques to model cognitive systems.Secondly, we would like to thank the workshop sponsors - The Computing Laboratory at the University of Kent at Canterbury and CNR-Istituto CNUCE, in Pisa.Thirdly, the workshop benefited from the reviewing efforts of the workshop committee. Tommaso Bolognesi (CNR/I.E.I. at Pisa, Italy)Howard Bowman (Univ. of Kent at Canterbury, UK)Alan Dix (aQtive Limited, UK)David Duce (Rutherford Appleton Laboratory, UK)David Duke (University of York, UK)Giorgio Faconti (CNR/CNUCE at Pisa, Italy)Chris Johnson (University of Glasgow, UK)Peter Johnson (University of Bath, UK)Peter B. Ladkin (University of Bielefeld, Germany)Scott Smolka (State University of New York at Stony Brook, US)Graziella Tonfoni (University of Bologna, Italy and The George Washington Unversity, US)Ken Turner (University of Stirling, UK)Finally, thanks should go to Professor Mike Mislove for his help during the proceedings editorial process and to Kerry Riches for her help in preparing the participants proceedings.

Minimum-weight spanning tree algorithms A survey and empirical study

The minimum-weight spanning tree problem is one of the most typical and well-known problems of combinatorial optimisation. Efficient solution techniques had been known for many years. However, in the last two decades asymptotically faster algorithms have been invented. Each new algorithm brought the time bound one step closer to linearity and finally Karger, Klein and Tarjan proposed the only known expected linear-time method. Modern algorithms make use of more advanced data structures and appear to be more complicated to implement. Most authors and practitioners refer to these but still use the classical ones, which are considerably simpler but asymptotically slower. The paper first presents a survey of the classical methods and the more recent algorithmic developments. Modern algorithms are then compared with the classical ones and their relative performance is evaluated through extensive empirical tests, using reasonably large-size problem instances. Randomly generated problem instances used in the tests range from small networks having 512 nodes and 1024 edges to quite large ones with 16 384 nodes and 524 288 edges. The purpose of the comparative study is to investigate the conjecture that modern algorithms are also easy to apply and have constants of proportionality small enough to make them competitive in practice with the older ones. Scope and purpose The minimum-weight spanning tree (MST) problem is a well-known combinatorial optimisation problem concerned with finding a spanning tree of an undirected, connected graph, such that the sum of the weights of the selected edges is minimum. The importance of this problem derives from its direct applications in the design of computer, communication, transportation, power and piping networks; from its appearance as part of solution methods to other problems to which it applies less directly such as network reliability, clustering and classification problems and from its occurrence as a subproblem in the solution of other problems like the travelling salesman problem, the multi-terminal flow problem, the matching problem and the capacitated MST problem. Although efficient solution techniques capable of solving large instances had existed, there has been sustained effort over the last two decades to invent asymptotically faster algorithms. With each new algorithm found the time bound approached linearity. Finally, an expected linear-time method has been proposed. The purpose of this work is to survey the classical and modern solution techniques and empirically compare the performance of the existing methods.

An artificial neural network approach for routing in distributed computer networks

This paper presents a new approach based on the Hopfield model of artificial neural networks to solve the routing problem in a context of computer network design. The computer networks considered are packet switching networks, modeled as non-oriented graphs where nodes represent servers, hosts or switches, while bi-directional and symmetric arcs represent full duplex communication links. The proposed method is based on a network representation enabling to match each network configuration with a Hopfield neural network in order to find the best path between any node pair by minimizing an energy function. The results show that the time delay derived from flow assignment carried out by this approach is, in most cases, better than those determined using conventional routing heuristics. Therefore, this neural-network approach is suitable to be integrated into an overall topological design process of moderate-speed and high-speed networks subject to quality of service constraints as well as to changes in configuration and link costs.

DEACON: An Integrated Approach to the Analysis and Design of Enterprise Architecture-Based Computer Networks

The most common approach to network development in the modern organization remains an undocumented, ad hoc method of deploying available technology rapidly to fit within a given cost structure. Current methods largely ignore the importance of integrating the networking strategy of a firm with the overall information systems architecture of the enterprise. To address this problem, a new approach to network analysis and design is presented. The new method integrates existing principles of information systems analysis and design with the unique requirements imposed by distributed systems. The integrated approach seeks to provide the organization with a set of guidelines for allocating resources to a computer network based upon the business goals of a firm. Specifically, the method calls for (1) defining the business problem, (2) modeling business requirements, (3) modeling location requirements, (4) developing a network architecture, (5) simulating network operation, and (6) implementing the network. The method is illustrated and compared to other network development methods. DEACON is found to be an advantageous approach.

Routing in computer networks using artificial neural networks

This paper proposes a heuristic approach based on Hopfield model of neural networks to solve the problem of routing which constitutes one of the key aspects of the topological design of computer networks. Adaptive to changes in link costs and network topology, the proposed approach relies on the utilization of an energy function which simulates the objective function used in network optimization while respecting the constraints imposed by the network designers. This function must converge toward a solution which, if not the best is at least as close as possible to the optimum. The simulation results reveal that the end-to-end delay computed according to this neural network approach is usually better than those determined by the conventional routing heuristics, in the sense that our routing algorithm realizes a better trade-off between end-to-end delay and running time, and consequently gives a better performance than many other well-known optimal algorithms.

Integrating routing and survivability in fault-tolerant computer network design

In the context of computer networks, most conventional algorithms are designed to work under no-failure conditions for dealing with the routing problem. This paper investigates a more realistic situation where the flow assignment takes into account the possibility of a link failure. The method proposed to deal with this problem guarantees the survivability and allows analyzing the network behavior after a link failure. Further, it can be applicable to networks during their design phase as well as during the operational phase. Result analysis reveals the capacity of this method to design networks which satisfy the survivability constraints and to largely improve the delay obtained by other methods.

Optimal service and arrival rates in Jackson queueing networks

In this paper we present an algorithm for solving a class of queueing network design problems. Specifically, we focus on determining both service and arrival rates in an open Jackson network of queueing stations. This class of problems has been widely studied and used in a variety of applications, but not well solved due to the difficulty of the resulting optimization problems. As an example, consider the classic application in computer network design which involves determining the minimum cost line capacities and flow assignments while satisfying a queueing performance measure such as an upper limit on transmission delay. Other application areas requiring the selection of both service and arrival rates in a network of queues include the design of communication, manufacturing, and health care systems. These applications yield optimization problems that are difficult to solve because typically they are nonconvex, which means they may have many locally optimal solutions that are not necessarily globally optimal. Therefore, to obtain a globally optimal solution, we develop an efficient branch and bound algorithm that takes advantage of the problem structure. Computational testing on randomly generated problems and actual problems from a health care organization indicate that the algorithm is able to solve realistic sized problems in reasonable computing time on a laptop computer. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 1–17, 2000

Web-based network analysis and design

The gradual acceptance of high-performance networks as a fundamental component of today's computing environment has allowed applications to evolve from static entities located on specific hosts to dynamic, distributed entities that are resident on one or more hosts. In addition, vital components of software and data used by an application may be distributed across the local/wide area network. Given such a fluid and dynamic environment, the design and analysis of high-performance communication networks (using off-the-shelf components offered by third party manufacturers) has been further complicated by the diversity of the available components. To alleviate these problems and to address the verification and validation issues involved in engineering such complex networks, a web-based framework for the design and analysis of computer networks was developed. Using the framework, a designer can explore design alternatives by constructing and analyzing configurations of the design using components offered by different researchers and manufacturers. The framework provides a flexible and robust environment for selecting and verifying the optimal solution from a large and complex solution space. This paper presents issues involved in the design and development of the framework.

Considerations about the New Computer Networks Design Paradigm

Considerations about the New Computer Networks Design Paradigm

The I-Space: a framework for analyzing the evolution of social computing

Advances in the design of computer architectures and networks have led to new ways of representing, creating, manipulating and distributing knowledge. This paper takes a sociotechnical view of computing and considers the impact of computer architectures which are based on connectionist principles and the growth in computer networks on the representation of the learning process and strategies for dealing with complexity. It calls for a new economic view of knowledge and intellectual property rights more appropriate for the analysis of information flows in networks. Finally, the Information Space (I-Space) is presented as a framework for the analysis and evaluation of information flows.

Dynamic design of a reliable computer network on using information theory

There exists a graph theoretic model of self-diagnosable system by Preparata et al. [1]. Using a corresponding information theoretic model, a reliability measure of a computer network was obtained [2]. Based on the a priori probability of failure of different computers and edge weights assigned for some test outcomes, probabilistically t-reliable system is characterised. Next optimal design of p − t reliable system is given. The associated design issues linked with dynamic environment are also highlighted.

Process mapping in screening mammography.

Successful screening mammography programs aim to screen large numbers of women efficiently and inexpensively. Development of an effective screening mammography program requires skilled personnel, solid infrastructure, and a robust computer system. A group of physicians, technologists, computer support personnel, and administrators carefully analyzed a growing screening mammography program as a series of steps, starting with the request for the examination and ending with the receipt of a hard-copy consultation. The analysis involved a detailed examination of every step and every possible outcome in the screening process. The information gained through process mapping may be used for identification of systemic and personnel problems, allocation of resources, modification of workplace architecture, and design of computer networks. Process mapping is helpful for those involved in designing and improving screening mammography programs. Viewing a process (i.e., obtaining a screening mammogram) as a series of steps may allow for the identification of inefficient components that may limit growth.