Deploying networks onboard mass transit vehicles, e.g., trains and buses, and connecting these moving networks to the Internet using cellular or satellite services is seen as a promising technology to meet the broadband demand in the transport sector. This thesis examines the problem of service disruptions in such moving networks and proposes original solutions to manage these disruptions. Service disruption is caused by two main reasons. First, unavailability of wireless resources in the back-haul (e.g., cellular) network may prevent successful handoff of all passenger calls when the moving vehicle leaves the coverage of one radio tower and enters another. Second, the moving network may face frequent network disconnections when the vehicle travels through environments with severe radio coverage, e.g., tunnels. To address service disruption due to back-haul resource unavailability, an advance resource reservation frame work is proposed whereby the deterministic mobility of public transport is exploited to reserve bandwidth at target radio base-stations along the route of the vehicle. The viability of the proposed advance reservation framework is validated by (i) a predictability analysis of resource demand of moving networks using real passenger data, which show that it is possible to predict the demand at an upcoming location based on past data and the passenger count at the current location, and (ii) design of cellular extensions which show that advance reservation not only can be accommodated in existing cellular architectures with minimal modifications, it can also guarantee fast and scalable access to massive reservation data. To quantify the effect of temporary network disconnections on the probability of service disruption, new mathematical models have been developed and validated by computer simulation. Finally, a novel proactive admission control (PAC) approach is proposed to reduce service disruption by rejecting new call requests when the moving network is predicted to experience an imminent network disconnection. Using mathematical modelling, it has been demonstrated that PAC reduces service disruption probability exponentially as a function of the proactive decision time with only a linear increase in the new call blocking probability. Practicality of the PAC approach has been confirmed using empirical data from actual vehicular trips.