Result: Consumerized and peer-tutored service composition

With continued development towards the Internet of Things, services are making their way from enterprise solutions to our offices and homes. This process is a major driving force in consumerization of IT, because sustainable application development at this scale will not be possible without direct involvement and innovation from consumers themselves. In this paper, we present our work on consumerization of service composition tools. First, we describe how consumer-facing services can be presented in a usable and intuitive way. Then, combining social computing with machine intelligence, we define a recommender system that supports consumers in sharing their knowledge and creativity in peer-tutored service composition, thus empowering consumers to create their own applications. This system recommends consumers with the required service composition knowledge based on mining procedural knowledge stored in previously defined compositions. Once such a group of consumers is identified, social computing tools are used to allow them to share this knowledge with their peers. To demonstrate the effectiveness of this peer-tutored service composition model, we performed consumer satisfaction studies on our consumerized service composition tool Geppeto, which we extended with the described recommender system. Results show significant improvements in service composition in terms of performance and quality of experience.