Proactive adaptation in service composition using a fuzzy logic based optimization mechanism

The importance of Quality of Service management in service oriented environments has brought the need of QoS aware solutions. Proactive adaptation approaches enable composite services to detect in advance, according to their QoS values, the need for a change in order to prevent upcoming problems, and maintain the functional and quality levels of the composition. This paper presents a proactive adaptation mechanism that implements self-optimization based on fuzzy logic. The optimization model uses two fuzzy inference systems that evaluate the QoS values of composite services, based on historical and freshly collected data, and decide if adaptation is needed or not. Experimental results show significant improvements in the global QoS of the use case scenarios, providing reductions of up to 8.9% in response time and 14.7% in energy consumption, and an improvement of 41% in availability; this is achieved with an average increment in cost of 11.75 %.