The ongoing development of new and demanding Internet applications requires the Internet to deliver better service levels that are significantly better than the best effort service that the Internet currently provides and was built for. These improved service levels include guaranteed delays, jitter and bandwidth. Through extensive research into Quality of Service and Differentiated Service (DiffServ) it has become possible to provide guaranteed services, however this turns out to be inadequate without the application of Traffic Engineering methodologies and principles. Traffic Engineering is an integral part of network operation. Its major goal is to deliver the best performance from an existing service provider's network resources and, at the same time, to enhance a customers' view of network performance. In this thesis, several different traffic engineering methods for optimising the operation of native IP and IP networks employing MPLS are proposed. A feature of these new methods is their fast run times and this opens the way to making them suitable for application in an online traffic engineering environment. For native IP networks running shortest path based routing protocols, we show that an LP-based optimisation based on the well known multi-commodity flow problem can be effective in removing network congestion. Having realised that Internet service providers are now moving towards migrating their networks to the use of MPLS, we have also formulated optimisation methods to traffic engineer MPLS networks by selecting suitable routing paths and utilising the feature of explicit routing contained in MPLS. Although MPLS is capable of delivering traffic engineering across different classes of traffic, network operators still prefer to rely on the proven and simple IP based routing protocols for best effort traffic and only use MPLS to route traffic requiring special forwarding treatment. Based on this fact, we propose a method that optimises the routing patterns applicable to different classes of traffic based on their bandwidth requirements. A traffic engineering comparison study that evaluates the performance of a neural network-based method for MPLS networks and LP-based weight setting approach for shortest path based networks has been performed using a well-known open source network simulator, called ns2. The comparative evaluation is based upon the packet loss probability. The final chapter of the thesis describes the software development of a network management application called OptiFlow which integrates techniques described in earlier chapters including the LP-based weight setting optimisation methodology; it also uses traffic matrix estimation techniques that are required as input to the weight setting models that have been devised. The motivation for developing OptiFlow was to provide a prototype set of tools that meet the congestion management needs of networking industries (ISPs and telecommunications companies - telcos).

<p>The principle of load balancing is to distribute the data load more evenly over the network in order to increase the network performance and efficiency. With dynamic load balancing the routing is undated at certain intervals. This thesis was developed to evaluate load balancing methods in the IP-network of TeliaSonera.Load balancing using short path routing, bottleneck load balancing and load balancing using MPLS have been evaluated. Short path routing is a flow sharing technique that allows routing on paths other than the shortest one. </p><p>Load balancing using short path routing is achieved by dynamic updates of the link weights. Bottleneck is in its nature a dynamic load balancing algorithm. Unlike load balancing using short path routing it updates the flow sharing, not the metrics. The algorithm uses information about current flow sharing and link loads to detect bottlenecks within the network. The information is used to calculate new flow sharing parameters. When using MPLS, one or more complete routing paths (LSPs) are defined at each edge LSR before sending any traffic. MPLS brings the ability to perform flow sharing by defining the paths to be used and how the outgoing data load is to be shared among these.</p><p>The model has been built from data about the network supplied by TeliaSonera. The model consists of a topology part, a traffic part, a routing part and cost part. The traffic model consists of a OD demand matrix. The OD demand matrix has been estimated from collected link loads. This was done with estimation models; the gravity model and an optimisation model.</p><p>The algorithms have been analysed at several scenarios; normal network, core node failure, core link failure and DWDM system failure. A cost function, where the cost increases as the link load increases has been used to evaluate the algorithms. The signalling requirements for implementation of the load balancing algorithm have also been investigated.</p>

<p>As one of the highest fatalities causes, traffic accidents and collisions always requires a large amounteffort to be reduced or prevented from occur. Traffic safety management routines therefore always needefficient and effective implementation due to the variations of traffic, especially from trafficengineering point of view apart from driver education.Traffic Accident Prediction Model, considered as one of the handy tool of traffic safety management,has become of well followed with interested. Although it is believed that traffic accidents are mostlycaused by human factors, these accident prediction models would help from traffic engineering point ofview to enlarge the traffic safety level of road segments. This thesis is aiming for providing a guidelineof the accident prediction model implementation in traffic safety management, regarding to trafficengineering field. Discussion about how this prediction models should merge into the existing routinesand how well these models would perform would be given. As well, cost benefit analysis of theimplementation would be at the end of this thesis. Meanwhile, a practical field study would bepresented in order to show the procedures of the implementation of traffic accident prediction model.The field study is about this commercial model set SafeNET, from TRL Limited UK, implemented inRoad Safety Audit procedures combined with microscopic simulation tool. Detailed processing andinput and output data will be given accompany with the countermeasures for accident frequencyreduction finalization.</p>

by S.B. Gershwin and H.-N. Tan. / Bibliography: leaves 5-6. / Caption title. / Supported by the U.S. Dept. of Transportation under Contract DOT-TSC-1456

by H.-N. Tan and S.B. Gershwin. / Bibliography: leaves 13-15. / "February, 1979." Caption title. / Supported by the U.S. Dept. of Transportation under Contract DOT-TSC-1456

Today, numerous alternative modes of mobility are emerging to provide a solution to the problems created by the automobile. This research envisions a future where transportation in urban areas will be dominated by small personal mobility devices (PMDs) instead of automobiles. This Intelligent Mobility System (IMS) would be a car-free zone where people travel by a shared-system of PMDs providing levels of mobility greater than walking but less than a car. This research effort focuses on the operational aspects of this future system by studying PMD performance characteristics as inputs for a computer simulation model of an IMS environment. Therefore, the primary objective of this research is to evaluate the operations of PMDs that are currently used in a variety of settings. GPS recorders are used to log speed and location data each second of pedestrian, bicycle, Segway, and electric cart trips. Segway speed and acceleration are analyzed using three factors, sidewalk width, surface quality, and pedestrian density to study their effect on Segway speed. Pedestrians have the lowest mean speed and the most narrow speed distribution. Segways, bicycles and electric carts have increasingly faster mean speeds and wider speed distributions, respectively. Segways and bicycles were found to have similar acceleration distributions. Segways seem to provide a level of speed and mobility between that of pedestrians and cyclists, meaning that Segways might capture new users by providing a level of mobility and convenience previously unseen. Narrow sidewalk widths, poor sidewalk quality, and heavy pedestrian density all decreased Segway speeds. The researchers suspect that surface quality is likely an independent constraint for Segway speed and that sidewalk width and pedestrian density interact to limit Segway speeds under certain conditions. This research concludes that these external factors may affect PMD speed and should be considered when analyzing PMD mobility, especially in an IMS setting.

This thesis presents an approach to the design and management of core networks where the packet transport is the main service and the backbone should be able to respond to unforeseen changes in network parameters in order to provide smooth and reliable service for the customers. Inspired by Darwin's seminal work describing the long-term processes in life, and with the help of graph theoretic metrics, in particular the "random-walk betweenness", we assign a survival value, the network criticality, to a communication network to quantify its robustness. We show that the random-walk betweenness of a node (link) consists of the product of two terms, a global measure which is fixed for all the nodes (links) and a local graph measure which is in fact the weight of the node (link). The network criticality is defined as the global part of the betweenness of a node (link). We show that the network criticality is a monotone decreasing, and strictly convex function of the weight matrix of the network graph. We argue that any communication network can be modeled as a topology that evolves based on survivability and performance requirements. The evolution should be in the direction of decreasing the network criticality, which in turn increases the network robustness. We use network criticality as the main control parameter and we propose a network management system, AutoNet, to guide the network evolution in real time. AutoNet consists of two autonomic loops, the slow loop to control the long-term evolution of robustness throughout the whole network, and the fast loop to account for short-term performance and robustness issues. We investigate the dynamics of network criticality and we develop a convex optimization problem to minimize the network criticality. We propose a network design procedure based on the optimization problem which can be used to develop the long-term autonomic loop for AutoNet. Furthermore, we use the properties of the duality gap of the optimization problem to develop traffic engineering methods to manage the transport of packets in a network. This provides for the short-term autonomic loop of AutoNet architecture. Network criticality can also be used to rank alternative networks based on their robustness to the unpredicted changes in network conditions. This can help find the best network structure under some pre-specified constraint to deal with robustness issues.

This thesis presents an approach to the design and management of core networks where the packet transport is the main service and the backbone should be able to respond to unforeseen changes in network parameters in order to provide smooth and reliable service for the customers. Inspired by Darwin's seminal work describing the long-term processes in life, and with the help of graph theoretic metrics, in particular the "random-walk betweenness", we assign a survival value, the network criticality, to a communication network to quantify its robustness. We show that the random-walk betweenness of a node (link) consists of the product of two terms, a global measure which is fixed for all the nodes (links) and a local graph measure which is in fact the weight of the node (link). The network criticality is defined as the global part of the betweenness of a node (link). We show that the network criticality is a monotone decreasing, and strictly convex function of the weight matrix of the network graph. We argue that any communication network can be modeled as a topology that evolves based on survivability and performance requirements. The evolution should be in the direction of decreasing the network criticality, which in turn increases the network robustness. We use network criticality as the main control parameter and we propose a network management system, AutoNet, to guide the network evolution in real time. AutoNet consists of two autonomic loops, the slow loop to control the long-term evolution of robustness throughout the whole network, and the fast loop to account for short-term performance and robustness issues. We investigate the dynamics of network criticality and we develop a convex optimization problem to minimize the network criticality. We propose a network design procedure based on the optimization problem which can be used to develop the long-term autonomic loop for AutoNet. Furthermore, we use the properties of the duality gap of the optimization problem to develop traffic engineering methods to manage the transport of packets in a network. This provides for the short-term autonomic loop of AutoNet architecture. Network criticality can also be used to rank alternative networks based on their robustness to the unpredicted changes in network conditions. This can help find the best network structure under some pre-specified constraint to deal with robustness issues.

As one of the highest fatalities causes, traffic accidents and collisions always requires a large amounteffort to be reduced or prevented from occur. Traffic safety management routines therefore always needefficient and effective implementation due to the variations of traffic, especially from trafficengineering point of view apart from driver education.Traffic Accident Prediction Model, considered as one of the handy tool of traffic safety management,has become of well followed with interested. Although it is believed that traffic accidents are mostlycaused by human factors, these accident prediction models would help from traffic engineering point ofview to enlarge the traffic safety level of road segments. This thesis is aiming for providing a guidelineof the accident prediction model implementation in traffic safety management, regarding to trafficengineering field. Discussion about how this prediction models should merge into the existing routinesand how well these models would perform would be given. As well, cost benefit analysis of theimplementation would be at the end of this thesis. Meanwhile, a practical field study would bepresented in order to show the procedures of the implementation of traffic accident prediction model.The field study is about this commercial model set SafeNET, from TRL Limited UK, implemented inRoad Safety Audit procedures combined with microscopic simulation tool. Detailed processing andinput and output data will be given accompany with the countermeasures for accident frequencyreduction finalization.

The principle of load balancing is to distribute the data load more evenly over the network in order to increase the network performance and efficiency. With dynamic load balancing the routing is undated at certain intervals. This thesis was developed to evaluate load balancing methods in the IP-network of TeliaSonera.Load balancing using short path routing, bottleneck load balancing and load balancing using MPLS have been evaluated. Short path routing is a flow sharing technique that allows routing on paths other than the shortest one. Load balancing using short path routing is achieved by dynamic updates of the link weights. Bottleneck is in its nature a dynamic load balancing algorithm. Unlike load balancing using short path routing it updates the flow sharing, not the metrics. The algorithm uses information about current flow sharing and link loads to detect bottlenecks within the network. The information is used to calculate new flow sharing parameters. When using MPLS, one or more complete routing paths (LSPs) are defined at each edge LSR before sending any traffic. MPLS brings the ability to perform flow sharing by defining the paths to be used and how the outgoing data load is to be shared among these. The model has been built from data about the network supplied by TeliaSonera. The model consists of a topology part, a traffic part, a routing part and cost part. The traffic model consists of a OD demand matrix. The OD demand matrix has been estimated from collected link loads. This was done with estimation models; the gravity model and an optimisation model. The algorithms have been analysed at several scenarios; normal network, core node failure, core link failure and DWDM system failure. A cost function, where the cost increases as the link load increases has been used to evaluate the algorithms. The signalling requirements for implementation of the load balancing algorithm have also been investigated.