Efficient Approach Towards an Agent-Based Dynamic Web Service Discovery Framework with QoS Support

Abstract. Web services are about the integration of applications via the Web. Hereby, the programming effort should be minimized through the reuse of standardized components and interfaces. One of the fundamental pillars of the Web service vision is a brokerage system that enables services to be published to a searchable repository and later retrieved by potential users. One of the subtasks in a service-oriented architecture is service discovery. Service discovery, the identification of existing Web Services that can be used by new Web applications, is one of the most critical problems deterring Web Service (WS) technology. Current solution is based on UDDI catalogue browsing that supports only primitive matching mechanisms and provides no control over the quality of registered services Quality of Service (QoS) is becoming an important criterion for selection of the best available service. Currently the problem is twofold. The Universal Description, Discovery and Integration (UDDI) registries do not have the ability to publish the QoS information, and the authenticity of the advertised QoS information available elsewhere may be questionable. We aim to refine the discovery process through designing a new framework that enhances retrieval algorithms by combining syntactic and semantic matching of services with QoS. We propose a model of QoS-based Web services discovery that combines an augmented UDDI registry to publish the QoS information and a reputation manager to assign reputation scores to the services based on customer feedback of their performance. The Certifier verifies the QoS claims from the Web service suppliers. A discovery agent facilitates QoS-based service discovery using the reputation scores in a service matching, ranking and selection algorithm. The novelty of our model lies in its simplicity and in its coordination of the above mentioned components. The Proposed framework should give Web services consumers some confidence about the quality of services of the discovered Web services

An Extensible and Personalized Approach to QoS-enabled Semantic Web Service Discovery

We present a framework for the autonomous discovery and selection of Semantic Web services based on their QoS properties. The novelty of our approach is the wide use of semantic technologies for a customizable discovery, which enables both the service users and providers to flexibly specify their matching models for QoS and the corresponding environmental conditions. In the presented approach, the discovery and ranking of services can be personalized via the use of domain ontologies detailing the user's preferences and the provider's specification. The discovery component is modeled as an adaptive query processing system in which the basic steps of filtering, matchmaking, reputation-based QoS assessment, and ranking of services correspond to logical algebraic operators, which facilitates the introduction of different discovery algorithms and the automatic generation of appropriate parallelized matchmaking evaluations, enabling the scalability of our solution up to unpredictable arrival rate of user queries against high numbers of published service descriptions in the system

Semantic process mining tools: core building blocks

Process mining aims at discovering new knowledge based on information hidden in event logs. Two important enablers for such analysis are powerful process mining techniques and the omnipresence of event logs in today's information systems. Most information systems supporting (structured) business processes (e.g. ERP, CRM, and workflow systems) record events in some form (e.g. transaction logs, audit trails, and database tables). Process mining techniques use event logs for all kinds of analysis, e.g., auditing, performance analysis, process discovery, etc. Although current process mining techniques/tools are quite mature, the analysis they support is somewhat limited because it is purely based on labels in logs. This means that these techniques cannot benefit from the actual semantics behind these labels which could cater for more accurate and robust analysis techniques. Existing analysis techniques are purely syntax oriented, i.e., much time is spent on filtering, translating, interpreting, and modifying event logs given a particular question. This paper presents the core building blocks necessary to enable semantic process mining techniques/tools. Although the approach is highly generic, we focus on a particular process mining technique and show how this technique can be extended and implemented in the ProM framework tool

A Survey on Service Composition Middleware in Pervasive Environments

The development of pervasive computing has put the light on a challenging problem: how to dynamically compose services in heterogeneous and highly changing environments? We propose a survey that defines the service composition as a sequence of four steps: the translation, the generation, the evaluation, and finally the execution. With this powerful and simple model we describe the major service composition middleware. Then, a classification of these service composition middleware according to pervasive requirements - interoperability, discoverability, adaptability, context awareness, QoS management, security, spontaneous management, and autonomous management - is given. The classification highlights what has been done and what remains to do to develop the service composition in pervasive environments