A Self-adaptive hierarchical monitoring mechanism for Clouds

While Cloud computing offers the potential to dramatically reduce the cost of software services through the commoditization of IT assets and on-demand usage patterns, one has to consider that Future Internet applications raise the need for environments that can facilitate real-time and interactivity and thus pose specific requirements to the underlying infrastructure. The latter, should be able to efficiently adapt resource provisioning to the dynamic Quality of Service (QoS) demands of such applications. To this direction, in this paper we present a monitoring system that facilitates on-the-fly self-configuration in terms of both the monitoring time intervals and the monitoring parameters. The proposed approach forms a multi-layered monitoring framework for measuring QoS at both application and infrastructure levels targeting trigger events for runtime adaptability of resource provisioning estimation and decision making. Besides, we demonstrate the operation of the implemented mechanism and evaluate its effectiveness using a real-world application scenario, namely Film Post Production.

► Implementation of a multi-layered monitoring mechanism that allows self-adaptation. ► The implementation is distributed across the layers of the Cloud paradigm. ► The system is being evaluated against a collaborative color correction application. ► The resource utilization was relatively small and the scalability performance stable.