Non-functional data collection for adaptive business processes and decision making

Abstract

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.

Service Level Achievements -- Distributed Knowledge for Optimal Service Selection

“…[8]- [14]. In most of these approaches, the service selection is based on SLAs provided by service providers.…”

“…We argue that SLAs do not always offer a sufficient foundation for service selection as discussed in the introduction. This observation is also taken into account by [8]. Furthermore, these approaches are limited to a local integration environment and lack an overall view beyond company borders.…”

Issues and scenarios for self-managing grid middleware

“…This will notably allows for self-adaptive monitoring, with the self-configuration of sampling intervals on probes [14] or triggering threshold [4]. More generally, any loop elements can be self-managed in the same way.…”