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.

Mobile data traffic is expected to increase substantially in the coming years, with data rates 1000 times higher by 2020, having media and content as the main drivers together with a plethora of new end-user services that will challenge existing networks. Concepts and visions associated with the ICT evolution like the network society, 50 billion connected devices, Industrial Internet, Tactile Internet, etc., exemplifies the range of new services that the networks will have to handle. These new services impose extreme requirement to the network like high capacity, low latency, reliability, security, seamless connectivity, etc. In order to face these challenges, the whole end-to-end network has to evolve and adapt, pushing for advances in different areas, such as transport, cloud, core, and radio access networks. This work investigates the impact of envisioned 2020 society scenarios on transport links for mobile backhaul, emphasizing the need for an integrated and flexible/adaptive network as the way to meet the 2020 networks demands. The evolution of heterogeneous networks and ultra-dense network deployments shall also comprise the introduction of adaptive network features, such as dynamic network resource allocation, automatic integration of access nodes, etc. In order to achieve such self-management features in mobile networks, new mechanisms have to be investigated for an integrated backhaul management. First, this thesis performs a feasibility study on the mobile backhaul dimensioning for 2020 5G wireless ultra-dense networks scenarios, aiming to analyze the gap in capacity demand between 4G and 5G networks. Secondly, the concept of an integrated backhaul management is analyzed as a combination of node attachment procedures, in the context of moving networks. In addition, the dynamic network resource allocation concept, based on DWDM-centric transport architecture, was explored for 5G scenarios assuming traffic variation both in time and between different geographical areas. Finally, a short view on techno-economics and network deployments in the 2020 time frame is provided.