Abstract-Computing has reached the time of distributed applications everywhere. Service-oriented architectures are more and more used to organize such complex and highly dynamic applications into business processes calling services discovered in registries at load-time. In this context, Quality of Service (QoS) and agility in business processes become key issues. Instead of binding business processes to services at load-time, this paper proposes to monitor sets of candidate services for their current QoS and to choose among them at call-time. This new form of late-binding paves the way to more agile and robust applications called adaptive business processes. Besides the conceptual background and implementation of this late-binding in an industrial-strength web service platform, this paper presents the LCP-net formalism introduced to provide programmers with a mean to express qualitatively their preferences among the different QoS properties of services, hence tackling the multicriteria decision making arising from the run-time choice among candidate services given several unrelated QoS properties.

This contribution addresses the problem of expressing preferences among nonfunctional properties in a Web Service architecture. In such a context, semantic annotations are needed and added on service declaration and business process in order to select the best available service. These conditional and unconditional preferences are managed using Conditional Preference-Networks (CP-Nets). But in several cases, uncertainty related to the preferences has to be taken into account to achieve a better satisfaction rate. We propose the use of fuzzy linguistic information inside the whole process when it will be necessary.

Monitoring application services becomes more and more a transverse key activity in SOA. Beyond traditional human system administration and load control, new activities such as autonomic management as well as SLA enforcement raise the stakes over monitoring requirements. In this paper, we address a new monitoring-based activity which is selecting among competitive service offers based on their currently measured QoS. Starting from this use case, the late binding of service calls in SOA given the current QoS of a set of candidate services, we first elicit the requirements and then describe M4ABP (Monitoring for Adaptive Business Process), a middleware component for monitoring services and delivering monitoring data to business processes wishing to call them. M4ABP provides solutions for general requirements: flexibility as well as performance in data access for clients, coherency of data sets and network usage optimization. Lessons learned from this first use case can be applied to similar monitoring scenario, as well as to the larger field of context-aware computing.

No abstract

No abstract