Abstract. Context management in pervasive computing environments must reflect the specific characteristics of these environments, e.g. distribution, mobility, resource-constrained devices, or heterogeneity of context sources. Although a number of context models have been presented in the literature, none of them supports all of these requirements to a sufficient extent at the same time. In this paper, we present a comprehensive and integrated approach for context modeling in pervasive computing environments. It combines the advantages of existing approaches and addresses the need for supporting effective software development. The proposed context model follows an ontology-based approach and has three layers of abstraction, i.e. conceptual layer, exchange layer, and functional layer. This layered approach facilitates a model-driven development of context-aware applications. Throughout the paper we compare our solution with the related work in order to clearly demonstrate why we needed to develop a new context management framework and where we have adopted existing ideas.
Driven by the emergence of mobile and pervasive computing there is a growing demand for context-aware software systems that can dynamically adapt to their run-time environment. We present the results of project MADAM which has delivered a comprehensive solution for the development and operation of context-aware, self-adaptive applications. The main contributions of MADAM are (a) a sophisticated middleware that supports the dynamic adaptation of component-based applications, and (b) an innovative model-driven development methodology which is based on abstract adaptation models and corresponding model-to-code transformations. MADAM has demonstrated the viability of a general, integrated approach to application-level adaptation. We discuss our experiences with two real-world case studies that were built using the MADAM approach.
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.
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