Challenges to describe QoS requirements for web services quality prediction to support web services interoperability in electronic commerce

Quality of service (QoS) is significant and necessary for web service applications quality assurance. Furthermore, web services quality has contributed to the successful implementation of Electronic Commerce (EC) applications. However, QoS is still the big issue for web services research and remains one of the main research questions that need to be explored. We believe that QoS should not only be measured but should also be predicted during the development and implementation stages. However, there are challenges and constraints to determine and choose QoS requirements for high quality web services. Therefore, this paper highlights the challenges for the QoS requirements prediction as they are not easy to identify. Moreover, there are many different perspectives and purposes of web services, and various prediction techniques to describe QoS requirements. Additionally, the paper introduces a metamodel as a concept of what makes a good web service

Quality-aware model-driven service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services

A coordination protocol for user-customisable cloud policy monitoring

Cloud computing will see a increasing demand for end-user customisation and personalisation of multi-tenant cloud service offerings. Combined with an identified need to address QoS and governance aspects in cloud computing, a need to provide user-customised QoS and governance policy management and monitoring as part of an SLA management infrastructure for clouds arises. We propose a user-customisable policy definition solution that can be enforced in multi-tenant cloud offerings through an automated instrumentation and monitoring technique. We in particular allow service processes that are run by cloud and SaaS providers to be made policy-aware in a transparent way

Model-driven performance evaluation for service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Software quality aspects such as performance are of central importance for the integration of heterogeneous, distributed service-based systems. Empirical performance evaluation is a process of measuring and calculating performance metrics of the implemented software. We present an approach for the empirical, model-based performance evaluation of services and service compositions in the context of model-driven service engineering. Temporal databases theory is utilised for the empirical performance evaluation of model-driven developed service systems

An Analysis of Service Ontologies

Services are increasingly shaping the world’s economic activity. Service provision and consumption have been profiting from advances in ICT, but the decentralization and heterogeneity of the involved service entities still pose engineering challenges. One of these challenges is to achieve semantic interoperability among these autonomous entities. Semantic web technology aims at addressing this challenge on a large scale, and has matured over the last years. This is evident from the various efforts reported in the literature in which service knowledge is represented in terms of ontologies developed either in individual research projects or in standardization bodies. This paper aims at analyzing the most relevant service ontologies available today for their suitability to cope with the service semantic interoperability challenge. We take the vision of the Internet of Services (IoS) as our motivation to identify the requirements for service ontologies. We adopt a formal approach to ontology design and evaluation in our analysis. We start by defining informal competency questions derived from a motivating scenario, and we identify relevant concepts and properties in service ontologies that match the formal ontological representation of these questions. We analyze the service ontologies with our concepts and questions, so that each ontology is positioned and evaluated according to its utility. The gaps we identify as the result of our analysis provide an indication of open challenges and future work

Semantic model-driven development of web service architectures.

Building service-based architectures has become a major area of interest since the advent of Web services. Modelling these architectures is a central activity. Model-driven development is a recent approach to developing software systems based on the idea of making models the central artefacts for design representation, analysis, and code generation. We propose an ontology-based engineering methodology for semantic model-driven composition and transformation of Web service architectures. Ontology technology as a logic-based knowledge representation and reasoning framework can provide answers to the needs of sharable and reusable semantic models and descriptions needed for service engineering. Based on modelling, composition and code generation techniques for service architectures, our approach provides a methodological framework for ontology-based semantic service architecture