A monitoring approach for runtime service discovery

Effective runtime service discovery requires identification of services based on different service characteristics such as structural, behavioural, quality, and contextual characteristics. However, current service registries guarantee services described in terms of structural and sometimes quality characteristics and, therefore, it is not always possible to assume that services in them will have all the characteristics required for effective service discovery. In this paper, we describe a monitor-based runtime service discovery framework called MoRSeD. The framework supports service discovery in both push and pull modes of query execution. The push mode of query execution is performed in parallel to the execution of a service-based system, in a proactive way. Both types of queries are specified in a query language called SerDiQueL that allows the representation of structural, behavioral, quality, and contextual conditions of services to be identified. The framework uses a monitor component to verify if behavioral and contextual conditions in the queries can be satisfied by services, based on translations of these conditions into properties represented in event calculus, and verification of the satisfiability of these properties against services. The monitor is also used to support identification that services participating in a service-based system are unavailable, and identification of changes in the behavioral and contextual characteristics of the services. A prototype implementation of the framework has been developed. The framework has been evaluated in terms of comparison of its performance when using and when not using the monitor component

Web Services Discovery and Recommendation Based on Information Extraction and Symbolic Reputation

This paper shows that the problem of web services representation is crucial and analyzes the various factors that influence on it. It presents the traditional representation of web services considering traditional textual descriptions based on the information contained in WSDL files. Unfortunately, textual web services descriptions are dirty and need significant cleaning to keep only useful information. To deal with this problem, we introduce rules based text tagging method, which allows filtering web service description to keep only significant information. A new representation based on such filtered data is then introduced. Many web services have empty descriptions. Also, we consider web services representations based on the WSDL file structure (types, attributes, etc.). Alternatively, we introduce a new representation called symbolic reputation, which is computed from relationships between web services. The impact of the use of these representations on web service discovery and recommendation is studied and discussed in the experimentation using real world web services

Two-fold Semantic Web service matchmaking – applying ontology mapping for service discovery

Semantic Web Services (SWS) aim at the automated discovery and orchestration of Web services on the basis of comprehensive, machine-interpretable semantic descriptions. Since SWS annotations usually are created by distinct SWS providers, semantic-level mediation, i.e. mediation between concurrent semantic representations, is a key requirement for SWS discovery. Since semantic-level mediation aims at enabling interoperability across heterogeneous semantic representations, it can be perceived as a particular instantiation of the ontology mapping problem. While recent SWS matchmakers usually rely on manual alignments or subscription to a common ontology, we propose a two-fold SWS matchmaking approach, consisting of (a) a general-purpose semantic-level mediator and (b) comparison and matchmaking of SWS capabilities. Our semantic-level mediation approach enables the implicit representation of similarities across distinct SWS by grounding service descriptions in so-called Mediation Spaces (MS). Given a set of SWS and their respective grounding, a SWS matchmaker automatically computes instance similarities across distinct SWS ontologies and matches the request to the most suitable SWS. A prototypical application illustrates our approach

Requirements-Driven Adaptation of Choreographed Interactions

Electronic services are emerging as the de-facto enabler of interaction interoperability across organization boundaries. Cross-organizational interactions are often “choreographed”, i.e. specified by a messaging protocol from a global point of view independent of the local view of each interacting organization. Local requirements motivating an interaction as well as the global contextual requirements governing the interaction inevitably evolve over time, requiring adaptation of the corresponding interaction protocol. Adaptation of an interaction protocol must ensure the satisfaction of both sets of interaction requirements while maintaining consistency between the global view and the local views of an interaction specification. Such adaptation is not possible with the current state-of-the-art representations of choreographed interactions, as they capture only operational messaging specifications detached from both local organizational requirements as well as global contextual requirements. This thesis presents three novel contributions that tackle adaptation of choreographed interaction protocols: an automated technique for deriving an interaction protocol from requirements, a formalization of consistency between local and global views, and a framework for guiding the adaptation of a choreographed interaction. A choreographed interaction is specified using models of organizational requirements motivating the interaction. We employ the formal semantics embedded in requirements models to automatically derive an interaction protocol. We propose a framework for relating the global and local views of interaction specification and maintaining consistency between them. We develop a metamodel for interaction specification, from which we enumerate adaptation operations. We build a catalogue that provides guidance on performing each operation and propagating changes between the global and local views. These contributions are evaluated using examples from the literature as well as a real-world case study

ServeNet: A Deep Neural Network for Web Services Classification

Automated service classification plays a crucial role in service discovery, selection, and composition. Machine learning has been widely used for service classification in recent years. However, the performance of conventional machine learning methods highly depends on the quality of manual feature engineering. In this paper, we present a novel deep neural network to automatically abstract low-level representation of both service name and service description to high-level merged features without feature engineering and the length limitation, and then predict service classification on 50 service categories. To demonstrate the effectiveness of our approach, we conduct a comprehensive experimental study by comparing 10 machine learning methods on 10,000 real-world web services. The result shows that the proposed deep neural network can achieve higher accuracy in classification and more robust than other machine learning methods.Comment: Accepted by ICWS'2

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities

Work flows in life science

The introduction of computer science technology in the life science domain has resulted in a new life science discipline called bioinformatics. Bioinformaticians are biologists who know how to apply computer science technology to perform computer based experiments, also known as in-silico or dry lab experiments. Various tools, such as databases, web applications and scripting languages, are used to design and run in-silico experiments. As the size and complexity of these experiments grow, new types of tools are required to design and execute the experiments and to analyse the results. Workflow systems promise to fulfill this role. The bioinformatician composes an experiment by using tools and web services as building blocks, and connecting them, often through a graphical user interface. Workflow systems, such as Taverna, provide access to up to a few thousand resources in a uniform way. Although workflow systems are intended to make the bioinformaticians' work easier, bioinformaticians experience difficulties in using them. This thesis is devoted to find out which problems bioinformaticians experience using workflow systems and to provide solutions for these problems.\u