Service-oriented systems for adaptive management of service composition

Service Oriented Systems (SOSs) based on the SOA paradigm are becoming popular thanks to a widely deployed internetworking infrastructure. They are composed by a possibly large number of heterogeneous third-party subsystems and usually operate in a highly varying execution environment, that makes it challenging to provide applications with Quality of Service (QoS) guarantees. A well-established approach to face the heterogeneous and varying operating environment is to design a SOS as a runtime self-adaptable software system, so that a prospective enterprise willing to realize a SOA application can dynamically choose the component services that best fit its requirements and the environment in which the application operates. In this chapter, the authors first review some representative frameworks that have been proposed for SOSs able to adaptively manage a SOA application with QoS requirements. These frameworks are commonly architected as self-adaptive systems following the MAPE-K (Monitor, Analyze, Plan, Execute, and Knowledge) reference model for autonomic computing. The chapter organizes the review using a specific taxonomy for each MAPE-K phase, with the aim to classify the different strategies and mechanisms that can be applied. Even if a self-adaptive system requires every MAPE-K phase, the authors then focus on the Plan phase, which is the core of each adaptation framework, presenting both optimal and sub-optimal approaches that have been proposed to effectively face the adaptation task at runtime.