With the advent of cloud computing and Software-as-a-Service, Service-Based Application (SBA) represents a new paradigm to build rapid, low-cost, interoperable and evolvable distributed applications. A new application is created by defining a workflow that coordinates a set of third-party Web services accessible over the Internet. In such distributed and loose coupling environment, the execution of SBA requires a high degree of flexibility. For example, suitable constituent services can be selected and integrated at runtime based on their Quality of Service (QoS); furthermore, the composition of service is required to be dynamically modified in response to unexpected runtime failures. In this context, the main objective of this dissertation is to design, to develop and to evaluate a service middleware for flexible execution of SBA by using chemical programming model. Using chemical metaphor, the service-based systems are modeled as distributed, selforganized and self-adaptive biochemical systems. Service discovery, selection, coordination and adaptation are expressed as a series of pervasive chemical reactions in the middleware, which are performed in a distributed, concurrent and autonomous way. Additionally, on the way to build flexible service based systems, we do not restrict our research only in investigating chemical-based solutions. In this context, the second objective of this thesis is to find out generic solutions, such as models and algorithms, to respond to some of the most challenging problems in flexible execution of SBAs. I have proposed a two-phase online prediction approach that is able to accurately make decisions to proactively execute adaptation plan before the failures actually occur.
