Authors:
Alessandro Miracca
and
Pierluigi Plebani
Affiliation:
Politecnico di Milano, Italy
Keyword(s):
Complex Event Processing, Data Prediction, Proactive Adaptation.
Related
Ontology
Subjects/Areas/Topics:
Energy and Economy
;
Green Data Centers
;
Green Software Engineering Methodologies and Tools
;
Qos and Green Computing
;
Sustainable Computing and Communications
Abstract:
The aim to reduce the energy consumption in data centres is usually analyzed in the literature from a facility and hardware standpoint. For instance, innovative cooling systems and less power hungry CPUs have been developed to save as much more energy as possible. The goal of this paper is to move the standpoint to the application level by proposing an approach, driven by a goal-based model and a Complex Event Processing (CEP) engine, that enables the adaptation of the business processes execution. As several adaptation strategies can be available to reduce the energy consumption, the selection of the most suitable adaptation strategy is often the most critical step as it should be done timely and correctly: adaptation has to occur as soon as a critical point is reached (i.e., reactive approach) or, even before it occurs (i.e., proactive approach). Finally, the adaptation actions must also consider the influence on the performance of the system that should not be violated.