This research is motivated by the recent developments in the Internet Engineering Task Force (IETF) to support seamless integration of moving networks deployed in vehicles to the global Internet. The effort, known as Network Mobility (NEMO), paves the way to support high-speed Internet access in mass transit systems, e.g. trains; buses; ferries; and planes; through the use of on-board mobile routers embedded in the vehicle. One of the critical research challenges of this vision is to achieve high-speed and reliable back-haul connectivity between the mobile router and the rest of the Internet. The problem is particularly challenging due to the fact that a mobile router must rely on wireless links with limited bandwidth and unpredictable quality variations as the vehicle moves around. In this thesis, the multi-homing concept is applied to approach the problem. With multi-homing, mobile router has more than one connection to the Internet. This is achieved by connecting the mobile router to a diverse array of wireless access technologies (e.g., GPRS, CDMA, 802.11, and 802.16) and/or a multiplicity of wireless service providers. While the aggregation helps addressing the bandwidth problem, quality variation problem can be mitigated by employing advanced traffic engineering techniques that dynamically control inbound and outbound traffic over multiple connections. More specifically, the thesis investigates traffic engineering solutions for mobile networks that can effectively address the performance objectives, e.g. maximizing profit for mobile network operator; guaranteeing quality of service for the users; and maintaining fair access to the back-haul bandwidth. Traffic engineering solutions with three different levels of control have been investigated. First, it is shown, using detailed computer simulation of popular applications and networking protocols(e.g., File Transfer Protocol and Transmission Control Protocol), that packet-level traffic engineering which makes decisions of which Internet connection to use for each and every packet, leads to poor system throughput. The main problem with packet-based traffic engineering stems from the fact that in mobile environment where link bandwidths and delay can vary significantly, packets using different connections may experience different delays causing unexpected arrivals at destinations. Second, a maximum utility flow-level traffic engineering has been proposed that aims to maximize a utility function that accounts for bandwidth utilization on the one hand, and fairness on the other. The proposed solution is compared against previously proposed flow-level traffic engineering schemes and shown to have better performance in terms of throughput and fairness. The third traffic engineering proposal addresses the issue of maximizing operator?s profit when different Internet connections have different charging rates, and guaranteeing per user bandwidth through admission control. Finally, a new signaling protocol is designed to allow the mobile router to control its inbound traffic.

Flow of traffic on freeways and limited access highways can be represented as a series of kinemetic waves. Solutions to these systems of equations become problematic under congested traffic flow conditions, and under complicated (real-world) networks. A simplified theory of kinematics waves was previously proposed. Simplifying elements includes translation of the problem to moving coordinate system, adoption of bi-linear speed-density relationships, and adoption of restrictive constraints at the on- and off-ramps. However, these simplifying assumptions preclude application of this technique to most practical situations. This research explores the limitations of the simplified theory of kinematic waves. First this research documents a relaxation of several key constraints. In the original theory, priority was given to on-ramp merging vehicles so that they can bypass any queue at the merge. This research proposes to relax this constraint using a capacity-based weighted fair queuing (CBWFQ) merge model. In the original theory, downstream queue affects upstream traffic as a whole and exiting traffic can always be able to leave as long as it gets to the diverge. This research proposes that this diverge constraint be replaced with a contribution-based weighted splitting (CBWS) diverge model. This research proposes a revised notation system, permitting the solution techniques to be extended to freeway networks with multiple freeways and their ramps. This research proposes a generalization to permit application of the revised theory to general transportation networks. A generalized CBWFQ merge model and a generalized CBWS diverge model are formulated to deal with merging and diverging traffic. Finally, this research presents computational procedure for solving the new system of equations. Comparisons of model predictions with field observations are conducted on GA 400 in Atlanta. Investigations into the performance of the proposed CBWFQ and CBWS models are conducted. Results are quite encouraging, quantitative measures suggest satisfactory accuracy with narrow confidence interval.

This research is motivated by the recent developments in the Internet Engineering Task Force (IETF) to support seamless integration of moving networks deployed in vehicles to the global Internet. The effort, known as Network Mobility (NEMO), paves the way to support high-speed Internet access in mass transit systems, e.g. trains; buses; ferries; and planes; through the use of on-board mobile routers embedded in the vehicle. One of the critical research challenges of this vision is to achieve high-speed and reliable back-haul connectivity between the mobile router and the rest of the Internet. The problem is particularly challenging due to the fact that a mobile router must rely on wireless links with limited bandwidth and unpredictable quality variations as the vehicle moves around. In this thesis, the multi-homing concept is applied to approach the problem. With multi-homing, mobile router has more than one connection to the Internet. This is achieved by connecting the mobile router to a diverse array of wireless access technologies (e.g., GPRS, CDMA, 802.11, and 802.16) and/or a multiplicity of wireless service providers. While the aggregation helps addressing the bandwidth problem, quality variation problem can be mitigated by employing advanced traffic engineering techniques that dynamically control inbound and outbound traffic over multiple connections. More specifically, the thesis investigates traffic engineering solutions for mobile networks that can effectively address the performance objectives, e.g. maximizing profit for mobile network operator; guaranteeing quality of service for the users; and maintaining fair access to the back-haul bandwidth. Traffic engineering solutions with three different levels of control have been investigated. First, it is shown, using detailed computer simulation of popular applications and networking protocols(e.g., File Transfer Protocol and Transmission Control Protocol), that packet-level traffic engineering which makes decisions of which Internet connection to use for each and every packet, leads to poor system throughput. The main problem with packet-based traffic engineering stems from the fact that in mobile environment where link bandwidths and delay can vary significantly, packets using different connections may experience different delays causing unexpected arrivals at destinations. Second, a maximum utility flow-level traffic engineering has been proposed that aims to maximize a utility function that accounts for bandwidth utilization on the one hand, and fairness on the other. The proposed solution is compared against previously proposed flow-level traffic engineering schemes and shown to have better performance in terms of throughput and fairness. The third traffic engineering proposal addresses the issue of maximizing operator?s profit when different Internet connections have different charging rates, and guaranteeing per user bandwidth through admission control. Finally, a new signaling protocol is designed to allow the mobile router to control its inbound traffic.

A 15.5-mile portion of the I-85 high-occupancy vehicle (HOV) lane in the metropolitan area of Atlanta, GA was converted to a high-occupancy toll (HOT) lane as part of a federal demonstration project designed to provide a reliable travel option through this congested corridor. Results from the I-85 demonstration project provided insight into the results that may follow the Georgia Department of Transportation's planned implementation of a $16 billion HOT lane network along metropolitan Atlanta's other major roadways [2]. To evaluate the impacts of the conversion, it was necessary to measure changes in corridor travel speed, reliability, vehicle throughput, passenger throughput, lane weaving, and user demographics. To measure such performance, a monitoring project, led by the Georgia Institute of Technology collected various forms of data through on-site field deployments, GDOT video, and cooperation from the State Road and Toll Authority (SRTA). Changes in the HOT lane's speed, reliability or other performance measure can affect the demographic and vehicle characteristics of those who utilize the corridor. The purpose of this particular study was to analyze the changes to the vehicle characteristics by comparing vehicle occupancy, vehicle classifications, and vehicle registration data to their counterparts from before the HOV-to-HOT conversion. As part of the monitoring project, the Georgia Tech research team organized a two-year deployment effort to collect data along the corridor during morning and afternoon peak hours. One year of data collection occurred before the conversion date to establish a control and a basis from which to compare any changes. The second year of data collection occurred after the conversion to track those changes and observe the progress of the lane's performance. While on-site, researchers collected data elements including visually-observed vehicle occupancy, license plate numbers, and vehicle classification [25]. The research team obtained vehicle records by submitting the license plate tag entries to a registration database [26]. In previous work, vehicle occupancy data were collected independently of license plate records used to establish the commuter shed. For the analyses reported in this thesis, license plate data and occupancy data were collected concurrently, providing a link between occupancy records of specific vehicles and relevant demographic characteristics based upon census data. The vehicle records also provided characteristics of the users' vehicles (light-duty vehicle vs. sport utility vehicle, model year, etc.) that the researchers aggregated to identify general trends in fleet characteristics. The analysis reported in this thesis focuses on identifying changes in vehicle characteristics that resulted from the HOV-to-HOT conversion. The data collected from post-conversion are compared to pre-conversion data, revealing changes in vehicle characteristics and occupancy distributions that most likely resulted from the implementation of the HOT lane. Plausible reasons affecting the vehicle characteristics alterations will be identified and further demographic research will enhance the data currently available to better pinpoint the cause and effect relationship between implementation and the current status of the I-85 corridor. Preliminary data collection outliers were identified by using vehicle occupancy data. However, future analysis will reveal the degree of their impact on the project as a whole. Matched occupancy and license plate data revealed vehicle characteristics for HOT lane users as well as indications that the tested data collectors are predominantly synchronized when concurrently collecting data, resulting in an argument to uphold the validity of the data collection methods. Chapter two provides reasons for why HOT lanes were sought out to replace I-85's HOV lanes. Chapter two will also provide many details regarding how the HOT lanes function and it will describe the role the Georgia Institute of Technology played in the assessment the HOV-to-HOT conversion. Chapter three includes the methodologies used to complete this document while chapter four provides results and analysis for the one year period before the conversion and the one year period after the conversion.