Although the areas of Service-Oriented Computing (SOC) and Agile and Lean Software Development (LSD) have been evolving separately in the last few years, they share several commonalities. Both are intended to exploit reusability and exhibit adaptability. SOC in particular aims to facilitate the widespread and diverse use of small, loosely coupled units of functionality, called services. Such services have a decided agility advantage, because they allow for changing a service provider at runtime without affecting any of a group of diverse and possibly anonymous consumers. Moreover, they can be composed at both development-time and run-time to produce new functionalities. Automatic service discovery and selection are key aspects for composing services dynamically. Current approaches attempting to automate discovery and selection make use of only structural and functional aspects of the services, and in many situations, this does not suffice to discriminate between functionally similar but disparate services. Service behavior is difficult to specify prior to service execution and instead is better described based on experience with the execution of the service. In this chapter, the authors present a behavioral approach to service selection and runtime adaptation that, inspired by agile software development techniques, is based on behavioral queries specified as test cases. Behavior is evaluated through the analysis of execution values of functional and non-functional parameters. In addition to behavioral selection, the authors’ approach allows for real-time evaluation of non-functional quality-of-service parameters, such as response time, availability, and latency.
Research on Methods for Discovering and Selecting Cloud Infrastructure Services Based on Feature Modeling
