Exploring intelligent service migration in a highly mobile network

Mobile services allow services to be migrated or replicated closer to users as they move around. This is now regarded as a viable mechanism to provide good Quality of Service to users in highly mobile environments such as vehicular networks. The vehicular environment is rapidly becoming a significant part of the internet and this presents various challenges that must be addressed; this is due to continuous handovers as mobile devices change their point of attachment to these networks resulting in a loss of service. Therefore, this explains the need to build a framework for intelligent service migration. This thesis addresses these issues. It starts by discussing the requirements for intelligent service migration. Then it investigates a low latency Quality of Service Aware Framework as well as an experimental transport protocol that would be favoured by vehicular networks. Furthermore, two analytical models are developed using the Zero-Server Markov Chain technique which is a way of analysing scenarios when the server is not continuously available to serve. Using the Zero-Server Markov Chain, the first analytical model looks at lost service due to continuous handovers and the communication dynamics of vehicular networks, while the second model analyses how service migration affects service delivery in these networks. Formulas are developed to yield the average number of packets in the system, the response time, the probability of blocking and a new parameter called the probability of lost service. These formulas are then applied to the Middlesex VANET Testbed to look at reactive and proactive service migration. These techniques are then incorporated into a new Service Management Framework to provide sustainable Quality of Service and Quality of Experience to mobile users in vehicular networks. This thesis also shows that this new approach is better than current approaches as it addresses key issues in intelligent service migration in such environments, and hence can play a significant part in the development of Intelligent Transport Systems for Smart Cities

Exploiting user contention to optimize proactive resource allocation in future networks

In order to provide ubiquitous communication, seamless connectivity is now required in all environments including highly mobile networks. By using vertical handover techniques it is possible to provide uninterrupted communication as connections are dynamically switched between wireless networks as users move around. However, in a highly mobile environment, traditional reactive approaches to handover are inadequate. Therefore, proactive handover techniques, in which mobile nodes attempt to determine the best time and place to handover to local networks, are actively being investigated in the context of next generation mobile networks. The Y-Comm Framework which looks at proactive handover techniques has de�fined two key parameters: Time Before Handover and the Network Dwell Time, for any given network topology. Using this approach, it is possible to enhance resource management in common networks using probabilistic mechanisms because it is now possible to express contention for resources in terms of: No Contention, Partial Contention and Full Contention. As network resources are shared between many users, resource management must be a key part of any communication system as it is needed to provide seamless communication and to ensure that applications and servers receive their required Quality-of-Service. In this thesis, the contention for channel resources being allocated to mobile nodes is analysed. The work presents a new methodology to support proactive resource allocation for emerging future networks such as Vehicular Ad-Hoc Networks (VANETs) by allowing us to calculate the probability of contention based on user demand of network resources. These results are veri�ed using simulation. In addition, this proactive approach is further enhanced by the use of a contention queue to detect contention between incoming requests and those waiting for service. This thesis also presents a new methodology to support proactive resource allocation for future networks such as Vehicular Ad-Hoc Networks. The proposed approach has been applied to a vehicular testbed and results are presented that show that this approach can improve overall network performance in mobile heterogeneous environments. The results show that the analysis of user contention does provide a proactive mechanism to improve the performance of resource allocation in mobile networks

Self-Sustaining Caching Stations: Towards Cost-Effective 5G-Enabled Vehicular Networks

In this article, we investigate the cost-effective 5G-enabled vehicular networks to support emerging vehicular applications, such as autonomous driving, in-car infotainment and location-based road services. To this end, self-sustaining caching stations (SCSs) are introduced to liberate on-road base stations from the constraints of power lines and wired backhauls. Specifically, the cache-enabled SCSs are powered by renewable energy and connected to core networks through wireless backhauls, which can realize "drop-and-play" deployment, green operation, and low-latency services. With SCSs integrated, a 5G-enabled heterogeneous vehicular networking architecture is further proposed, where SCSs are deployed along roadside for traffic offloading while conventional macro base stations (MBSs) provide ubiquitous coverage to vehicles. In addition, a hierarchical network management framework is designed to deal with high dynamics in vehicular traffic and renewable energy, where content caching, energy management and traffic steering are jointly investigated to optimize the service capability of SCSs with balanced power demand and supply in different time scales. Case studies are provided to illustrate SCS deployment and operation designs, and some open research issues are also discussed.Comment: IEEE Communications Magazine, to appea