Advances in pervasive technology have made it possible to consider large-scale application types that potentially span heterogeneous organizations, technologies, and device types. This class of application will have a multilayer architecture, where each layer is likely to use languages and technologies appropriate to its own concerns. An example application is a geographically large-scale crisis management system. Typically, such applications are required to dynamically adapt their behavior based on current circumstances, with adaptations potentially affecting all layers of the application. The complexities involved in dynamically adapting multilayer applications will significantly benefit from formal approaches to its specification. This article presents a new methodology for flexible, multilayer application adaptation, with layer-specific adaptation solution templates bound to application mismatches that are organized into hierarchical taxonomies. Templates can be linked either through direct invocations or through adaptation events, supporting flexible cross-layer adaptation. The methodology illustrates the use of different formalisms for different elements of its specification. In particular, we combine semiformal metamodeling techniques for the system model specification with formal Petri nets, which are used to capture template matchmaking using reachability analysis. This work demonstrates how existing formalisms can be used for the specification of a generic adaptation model for pervasive applications.

Our long-term objective is to develop a general methodology for deploying (Web) service aggregation and adaptation middleware, capable of suitably overcoming syntactic and behavioral mismatches in view of application integration within and across organizational boundaries. This article focuses on describing the core aggregation process, which generates the workflow of a composite service from a set of service workflows to be aggregated and a data-flow mapping linking service parameters.

Service-oriented enterprise systems, which tend to be heterogeneous, loosely coupled, long-lived, and continuously running, have to cope with frequent changes to their requirements and the environment. In order to address such changes, applications need to be inherently flexible and adaptive, supported by appropriate infrastructures. In this paper, we propose a model-driven approach for the dynamic adaptation of Web services based on ontology-aware service templates. Model-driven engineering raises the level of abstraction from concrete Web service implementations to high-level service models, which leads to more flexible and automated adaptations through template designs and transformations. The ontological semantics enhances the service matching capabilities required by the dynamic adaptation process. Service templates are based on OWL-S descriptions and provide the necessary means to capture and parameterize specific behavior patterns of service models. In this paper, we apply our approach in the context of the EU-funded ALIVE project and illustrate, as an example, how the proposed framework supports the adaptation of the authentication mechanism used by an interactive tourist recommendation system.

In this paper we introduce SMoL, a simplified BPEL- like language for specifying peer and service behaviour in P2P systems. We define a transformational semantics of SMoL in terms of YAWL workflows, which enables the simulation (e.g., testing possible execution scenarios) and analysis (e.g., verifying reachability or lock freedom) of the behaviour of P2P peers and services.

Service discovery and service aggregation are two crucial issues in the emerging area of service-oriented computing (SOC). We propose a new technique for the discovery of (Web) services that accounts for the need of composing several services to satisfy a client query. The proposed algorithm makes use of OWL-S ontologies, and explicitly returns the sequence of atomic process invocations that the client must perform in order to achieve the desired result. When no full match is possible, the algorithm features a flexible matching by returning partial matches and by suggesting additional inputs that would produce a full match.