While the Internet has evolved into an essential service delivery mfrastructure, the future success of mobile wireless networks also largely relies on their ability to provide customisable and self-adaptable services (named as pervasive services) in a cost-effective manner. The traditional static service engineering approach has become inadequate due to their problems related to adaptability, scalability and quality-of-service. This Thesis proposes to tackle these problems from the internal logic of pervasive services themselves by employing a combination of policies and models. This Thesis investigates how a pervasive service itself is represented as a policy-based management (PBM) system and how its creation is (semi-)automated by models of OMG Model-driven Architecture (MDA). A novel integration of PBM and MDA for the benefit of pervasive service engineering is proposed and validated. The output of the above creation is an executable sketch of a pervasive service with a generic policy decision engine reasoning over policies as its core. Service (re-)composition, together with loosely coupled policies for service description, provides a flexible and comprehensive mechanism to achieve context-awareness. The constituent components of a composed service can be discovered on the fly, using two complementary ad hoc service discovery algorithms based on the pull method and the push method respectively. The service discovery in this Thesis reuses the MDA models that are generated during static service creation stage and makes them available to the dynamic stages of the service lifecycle such as service discovery and service re-composition. Another contribution of this Thesis is the investigation of a comprehensive Quality of Pervasive Service (QoPS) model that integrates the QoS parameters perceived by end users and network QoS parameters. This QoPS model has been utilized for service component selection. The system is evaluated and validated both analytically and experimentally illustrating the methodology's feasibility, the system's performance effectiveness and efficiency
