Asynchronous Transfer Mode (ATM) has emerged as a possible contender for the next generation of digital data switching system and as the fundamental transport basis for the Broadband Integrated Services Digital Network, (B-ISDN) and telecommunications in the future. ATM networks can provide a high degree of flexibility. Due to the dynamic allocation of transmission and switching resources and the absence of a physical channel structure in such a network, services are not necessarily restricted to a particular bit rate. They may work at any bit rate within the limit of the network and can also support variable bit rate connections. There is a growing need for networks to carry a greater range of traffic such as wide-band traffic (video), bursty traffic (variable bit rate video), short holding time traffic (facsimile) and low bandwidth traffic (voice). To cope with variations in demand, networks must also be capable of dynamically allocating their total capacity amongst the various traffic types. The traffic requirements can be met through the use of architectures based on Asynchronous Transfer Mode (ATM).

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Thesis (M.S.)--University of Hawaii at Manoa, 2007. / Includes bibliographical references (leaves 71-74). / xi, 74 leaves, bound ill. 29 cm

Thesis (M.S.)--University of Hawaii at Manoa, 2007. / Includes bibliographical references (leaves 69-73). / ix, 73 leaves, bound ill. 29 cm

Enterprise intranets have gained popularity in recent times. The growth in size and complexity of these networks, in conjunction with their importance in maintaining business operations, have led to a greater requirement for network management. In addition, the type and severity of problems occurring in these networks have escalated, and the problems are much more difficult to detect. Much of this is attributed to unusual traffic patterns resulting from activity by network users. In the past, detection of network anomalies has relied upon correlation of alarms generated by network devices. More recently, statistical analysis of raw device level network measurements (e.g. variables from the management information bases maintained by network devices) has been explored. Whilst these approaches have proven valuable, they are most suitable for detecting problems, such as network device failures, that are local to the devices where measurements are collected. To complement these techniques a network-wide (or global) approach is required, whereby the dynamic behaviour of a network, in terms of topology and traffic flow, is measured and used for anomaly detection purposes. This method combines flow information taken throughout a network. Such an approach is capable of modelling the behaviour of traffic generated by network users, and hence can better define the cause of certain network anomalies. / This thesis develops a number of graph-based techniques that are capable of measuring the dynamic behaviour of a network and discusses their application in network management. By representing a computer network as a time series of uniquely labelled graphs, it is possible to measure the degree of change that has occurred between a pair of graphs, and hence the dynamics in a network. Concepts introduced include the median graph, intra- and inter- graph clustering, and hierarchical graph representations. The focus is on producing efficient algorithms and improved measures of network change. It is believed that these graph-based techniques for measuring network dynamics have great potential in network anomaly detection, and thus will improve reliability of enterprise intranets. / Thesis (PhDTelecommunications)--University of South Australia, 2006.

Computing the reliability of a network is a #P-complete problem, therefore estimation by means of simulation often becomes a favourable choice. In modern communication networks, link failure probabilities are usually small and hence network failures become rare events. This poses a challenge to estimate the network reliability. In this thesis we present different techniques for network reliability estimation. There are two main sampling techniques in reliability estimation: combinatorial and permutational sampling. Combinatorial sampling has the advantage of speed but has poor performance in rare event simulations. Permutational sampling gives good simulation performance but at a higher computational cost. We combine the two techniques and propose a hybrid sampling scheme called Tree Cut and Merge. By employing simple bounding together with clever conditional sampling, the TCM scheme achieves over 10(superscript 7) times speed up in certain classes of heterogeneous networks. The Crude Monte Carlo (combinatorial) component in the Tree Cut and Merge scheme may cause problems in some situations. In bad cases, the slow convergence problem re-appears. To address the problem, we modifed the scheme by introducing the Importance Sampling technique. The new Tree Cut and Merge with Importance Sampling scheme maintained the speed advantage of the Tree Cut and Merge and minimizes, at the same time, the potential problems caused by the Crude Monte Carlo component. Associated with the Importance Sampling technique, a new technique called the Cross-Entropy method has been developed in the late 90's to find the optimal Importance Sampling parameters. By employing the Cross-Entropy technique, we propose a new scheme called the Merge Process with Cross-Entropy. The new scheme improves the Merge Process in nearly all classes of network; in contrast, Tree Cut and Merge with Importance Sampling scheme sees the greatest improvement in heterogeneous networks. Besides estimating the reliability of a single network, this thesis also investigates a closely related problem: estimating the difference in reliability of two very similar networks. The problem is closely linked to the applications in the areas of network optimization, network evolution, reconfiguration and recovery, for example. The fact that the probabilities of rare events are hard to estimate makes estimating their difference even more difficult. Coupled and differential sampling techniques are proposed and applied to various schemes in this thesis. They prove to be superior to the conventional independent "estimate and subtract" method. Interestingly, these concepts also lead to new ideas regarding the estimation of the reliability of networks that are similar to networks with polynomially computable reliability. / Thesis (Ph.D.)--School of Mathematical Sciences, 2005.

Thesis (M.S. in Electrical Engineering)--Vanderbilt University, Dec. 2007. / Title from title screen. Includes bibliographical references.

Thesis (Ph.D.)--University of Texas at Dallas, 2007. / Includes vita. Includes bibliographical references.

Thesis (Ph.D.)--University of Nebraska-Lincoln, 2007. / Title from title screen (site viewed Nov. 9, 2007). PDF text: 191 p. : ill. ; 10 Mb. UMI publication number: AAT 3266780. Includes bibliographical references. Also available in microfilm and microfiche formats.