Towards a unified framework for the monitoring and recovery of BPEL processes

Web services have proven to be a viable solution for inter-operability issues. Since end users do not buy services, but only interact with them remotely, such complex systems end up having a distributed ownership, meaning different parts of a system can evolve independently. This has brought researchers to concentrate on run-time management issues such as dynamic monitoring and self-recovery. However, we advocate that no silver bullet has been found. All the major approaches have advantages and disadvan-tages. In this paper we propose a unified framework for monitoring and recovery that provides a clear separation be-tween data collection and analysis, a common management infrastructure, and a common recovery system. Separating monitoring from recovery allows the framework to integrate different monitoring approaches seamlessly through a plug-in approach. The common management infrastructure al-lows us to dynamically manage the multiple monitoring ap-proaches being used, while the common recovery approach allows us to activate advanced recovery techniques both on process instances and process definitions

A Fuzzy Extension for the XPath Query Language

XML has become a key technology for interoperability, providing a common data model to applications. However, diverse data modeling choices may lead to heterogeneous XML structure and content. In this paper, information retrieval and database-related techniques have been jointly applied to effectively tolerate XML data diversity in the evaluation of flexible queries. Approximate structure and content matching is supported via a straightforward extension to standard XPath syntax. Also, we outline a query execution technique representing a first step toward efficiently addressing structural pattern queries together with predicate support over XML elements content

A Fuzzy Extension for the XPath Query Language

Today the current state of the art in querying XML data is represented by XPath and XQuery, both of which rely on Boolean conditions for node selection. Boolean selection is too restrictive when users do not use or even know the data structure precisely, e.g. when queries are written based on a summary rather than on a schema. In this paper we describe a XML querying framework, called FuzzyXPath, based on Fuzzy Set Theory, which relies on fuzzy conditions for the definition of flexible constraints on stored data. A function called “deep-similar” is introduced to replace XPath’s typical “deep-equal” function. The main goal is to provide a degree of similarity between two XML trees, assessing whether they are similar both structure-wise and content-wise. Several query examples are discussed in the field of XML based metadata for e-learning