Semantic web service composition is about finding services from a repository that are able to accomplish a specified task if executed. The task is defined in a form of a composition request which contains a set of available input parameters and a set of wanted output parameters. Instead of the parameter values, concepts from an ontology describing their semantics are passed to the composition engine. The parameters of the services in the repository the composer works on are semantically annotated in the same way as the parameters in the request. The composer then finds a sequence of services, called a composition. If the input parameters given in the request are provided, the services of this sequence can subsequently be executed and will finally produce the wanted output parameters.In this paper, three different approaches to semantic web service composition are formally defined and compared with each other: an uninformed search in form of an IDDFS algorithm, a greedy informed search based on heuristic functions, and a multiobjective genetic algorithm.

In a Service Oriented Architecture (SOA) business processes are commonly implemented as orchestrations of web services, using the Web Services Business Process Execution Language (WS-BPEL). Business processes not only have to provide the required functionality, they also need to comply with certain Quality-of-Service (QoS) constraints which are part of a service-level agreement between the service provider and the client. Different service providers may offer services with the same functionality but different QoS properties, and clients can select from a large number of service offerings. However, choosing an optimal collection of services for the composition is known to be an NP-hard problem.We present two different approaches for the selection of services within orchestrations required to satisfy certain QoS requirements. We developed two algorithms, OPTIM_HWeight and OPTIM_PRO, which perform a heuristic search on the candidate services. The OPTIM_HWeight algorithm is based on weight factors and the OPTIM_PRO algorithm is based on priority factors. We evaluate and compare the two algorithms with each other and also with a genetic algorithm.

A major challenge for ubiquitous system design is creating applications that are legal-compatible and accepted by their intended users. Today's European data protection principles contradict the ideas of ubiquitous computing. Additionally, users have to deal with unconventional interaction concepts leading to a low amount of trust and acceptance in such systems. Current development approaches do not sufficiently cover these concerns, as they do not systematically incorporate expertise from the relevant disciplines. We present a novel development approach for ubiquitous systems that explicitly addresses these concerns. Our primary task was to manage the increased number of stakeholders and dependencies, respectively conflicts between requirements of the particular disciplines. The approach incorporates predefined artifacts and a defined workflow with responsibilities, as well as suggesting how to develop mutual understanding. We apply this multidisciplinary approach to develop the ubiquitous application Meet-U.

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