Ioan Toma

A qos-aware selection model for semantic web services

Automating Service Oriented Architectures by augmenting them with semantics will form the basis of the next generation of computing. Selection of service still is an important challenge, especially, when a set of services fulfilling users capabilities requirements have been discovered, among these services which one will be eventually invoked by user is very critical, generally depending on a combined evaluation of qualities of services (Qos). This paper proposes a QoS-based selection of services. Initially we specify a QoS ontology and its vocabulary using the Web Services Modeling Ontology (WSMO) for annotating service descriptions with QoS data. We continue by defining quality attributes and their respective measurements along with a QoS selection model. Finally, we present a fair and dynamic selection mechanism, using an optimum normalization algorithm.

A Multi-criteria Service Ranking Approach Based on Non-Functional Properties Rules Evaluation

Service oriented architectures (SOAs) are quickly becoming the de-facto solutions for providing end-to-end enterprise connectivity. However realizing the vision of SOA requires, among others, solutions for one fundamental challenge, namely service ranking. Once a set of services that fulfill the requested functionality is discovered, an ordered list of services needs to be created according to users preferences. These preferences are often expressed in terms of multiple non-functional properties (NFPs). This paper proposes a multi-criteria ranking approach for semantic web services. We start by briefly introducing ontological models for NFPs. These models are used to specify rules which describe NFP aspects of services and goals/requests. The ranking mechanism evaluates these NFPs rules using a reasoning engine and produces a ranked list of services according to users preferences.

Semantic Web Services

A paradigm shift is taking place in computer science: one generation ago, we learned to abstract from hardware to software, now we are abstracting from software to serviceware implemented through service-oriented computing. Yet ensuring interoperability in open, heterogeneous, and dynamically changing environments, such as the Internet, remains a major challenge for actual machine-to-machine integration. Usually significant problems in aligning data, processes, and protocols appear as soon as a specific piece of functionality is used within a different application context. The Semantic Web Services (SWS) approach is about describing services with metadata on the basis of domain ontologies as a means to enable their automatic location, execution, combination, and use. Fensel and his coauthors provide a comprehensive overview of SWS in line with actual industrial practice. They introduce the main sociotechnological components that ground the SWS vision (like Web Science, Service Science, and service-oriented architectures) and several approaches that realize it, e.g. the Web Service Modeling Framework, OWL-S, and RESTful services. The real-world relevance is emphasized through a series of case studies from large-scale R&D projects and a business-oriented proposition from the SWS technology provider Seekda.Each chapter of the book is structured according to a predefined template, covering both theoretical and practical aspects, and including walk-through examples and hands-on exercises. Additional learning material is available on the book website www.swsbook.org. With its additional features, the book is ideally suited as the basis for courses or self-study in this field, and it may also serve as a reference for researchers looking for a state-of-the-art overview of formalisms, methods, tools, and applications related to SWS.

Modeling QoS characteristics in WSMO

Service oriented architectures (SOAs) are becoming widespread solutions for realizing distributed applications. They promote a service view of the world in which functionalities exposed as services by different companies are assembled and reused in a standardized manner. Services are the core building blocks of SOAs and therefore modeling various aspects of services becomes a fundamental challenge. Among these aspects, quality-of-service (QoS) need to be addressed given the high dynamism of any SOA-based system. This paper introduces the basic steps of modeling QoS characteristics of services with the Web Service Modeling Ontology (WSMO) in order to provide a QoS-aware SOA. It discusses the current limitations of modeling QoS characteristics with WSMO and proposes a set of approaches towards a richer QoS modeling support. Each approach is analyzed in terms of complexity and the advantages and disadvantages of each approach are discussed.

Discovery in grid and web services environments: A survey and evaluation

An important step in realizing the vision of both Web services and Grid is the provision of a robust, automatic and reliable solution for finding services or resources in such environments. Different solutions to this problem were already proposed, each with its specific model and realization. Although all solutions address the same problem, it is very difficult for a non-expert and even for an expert in the field to decide if and why one solution is better then another. This paper proposes a systematic set of criteria, a framework, that can help in the evaluation of different discovery approaches. Furthermore some of the most relevant discovery approaches in Web services and Grid environments are surveyed and evaluated according to the proposed evaluation framework.

Semantic Web Fred - Automated Goal Resolution on the Semantic Web

Semantic Web Fred, SWF for short, is a context-independent, goal-driven system for automated execution of tasks that are delegated to electronic representatives along with dynamic service usage. A task is assigned to an agent for automated resolution, represented as a Goal. This is used to determine potential partners for collaborative task resolution, and for discovery of suitable goal-resolving services that can be internal implementations as well as external Semantic Web Services. The SWF technology integrates agent technology, ontologies, and Semantic Web Service technologies - the technological building blocks identified for the Semantic Web - into a coherent system. This paper describes the architecture of SWF, explains the mechanisms for establishing automated and cooperative goal resolution, and the alignment of SWF with the Web Service Modeling Ontology WSMO, a well-structured overall framework for Semantic Web Services. We also outline the contribution of SWF to the development of Semantic Web technologies.

On Describing and Ranking Services based on Non-Functional Properties

Service-oriented architectures are rapidly becoming the dominant computing paradigm. However, current SOA solutions are still restricted in their application context to being in-house solutions of companies. While service orientation is widely acknowledged for its potential to revolutionize the world of computing, its success depends on resolving a number of fundamental challenges, such as discovery, ranking and selection of services. Robust and automatic solutions for these challenges requires various services and user requests aspects, including functional and non-functional, to be semantically described. Non-functional properties especially are highly relevant especially during ranking and selection tasks. This paper introduces a semantically- enables approach for describing non-functional properties of services and further discusses how such descriptions can be used during in one service related task, namely ranking.

A semantically enabled service oriented architecture

The researchers in DERI Innsbruck have been building an execution infrastructure for the Semantic Web Services (SWS) based on the Services Oriented Architecture (SOA) paradigm of loosely coupled components. While SOA is widely acknowledged for its potential to revolutionize the world of computing, that success depends on resolving several fundamental challenges, and especially in the case of open SOA environment the existing specifications do not address several issues. We aim in DERI Innsbruck to define a skeleton of the SWS system and implement the overall infrastructure with the aim of automating service discovery, negotiation, adaptation, composition, invocation, and monitoring as well as service interaction requiring data, protocol, and process mediation. We call this infrastructure a Semantically Enabled Service oriented Architecture (SESA). While there are already several specifications in the space for Web Services there are still elements missing, for example there is no specification describing how the particular components/services of the SWS infrastructure would work together. That work is carried out by DERI researchers in standardization bodies such as OASIS and W3C. In the near future a service-oriented world will consist of an uncountable number of services. Computation will involve services searching for services based on functional and non-functional requirements and an interoperating with those that they select. Services will not be able to interact automatically and SOAs will not scale without signification mechanization of a fixed set of components/services. Hence, machine processable semantics are critical for the next generation of computing, services and SOAs, to reach their full potential. The contribution of DERI Innsbruck is to define and implement the fixed set of services of an infrastructure that must be provided to enable a dynamic discovery, selection, mediation, invocation and inter-operation of the Semantic Web Services to facilitate the SOA revolution towards open environments. We recognize in DERI Innsburck that SOA outside of tightly controlled environment cannot succeed until/unless the semantics issues are addressed. Only with semantics can critical subtasks can be automated leaving humans to focus on higher level problems.

Light-weight semantics and Bayesian Classification: A hybrid technique for dynamic Web Service discovery

Web Service discovery and ranking has been one of the key issues in Service Oriented Systems. Enormous efforts and research has been done towards semantic modeling of Web Services and a couple of semantic matchmaking and reasoning mechanisms have been developed to allow service consumers search for the required service providers dynamically. These approaches seem to be promising in theory, provided that exhaustive semantic descriptions of the services are available. However, in practice, this is not the case, as current Web Service standards provide quite limited information about services. Therefore, the process of discovery as well as ranking cannot always rely only on the extensive semantic descriptions to be available all the time. However, description of services using light-weight semantics (i.e., non-functional properties) is rather easier to have, and this could be used by classification and machine learning techniques to help in the classification of Web Services at real-time. In this paper, we present a hybrid approach towards enabling dynamic Web service discovery which is based on Bayesian Classification mechanism that classifies different available Web services, representing service providers, based on light-weight semantic descriptions.

WSMX 1.0: A Further Step toward a Complete Semantic Execution Environment

The Web Service Execution Environment (WSMX) project is a continuously ongoing effort that aims at delivering a middleware covering all the Semantic Web Services life cycle. WSMX represents the reference implementation of the Semantically enabled Service Oriented Architecture (SESA) [1]. In this demonstration we aim to present the latest achievements that include: Web Service monitoring, Web Service ranking and Web Service grounding.