Quality of Service (QoS) once defined in a contract between two parties may change during the life-cycle of Service-Based Applications (SBAs). Changes could be due to system failures or evolution of quality requirements from the involved parties. Therefore, Web Services need to be able to adapt dynamically to respond to such changes. Adaptation and evolution of services are playing an important task in this domain. An essential issue to be addressed is how to efficiently select an adaptation while, there exists different strategies. We propose a fuzzy service adaptation approach that works based on the degree of QoS satisfaction. In particular, we define fuzzy parameters for the QoS property descriptions of Web Services. This way, partial satisfaction of parameters is allowed through measuring imprecise requirements. The QoS satisfaction degree is measured using membership functions provided for each parameter. Experimental results show the effectiveness of the fuzzy approach using the satisfaction degree in selecting the best adaptation strategy.
A Fuzzy Service Adaptation Based on QoS Satisfaction
PERNICI, BARBARA;SIADAT, SEYED HOSSEIN
2011-01-01
Abstract
Quality of Service (QoS) once defined in a contract between two parties may change during the life-cycle of Service-Based Applications (SBAs). Changes could be due to system failures or evolution of quality requirements from the involved parties. Therefore, Web Services need to be able to adapt dynamically to respond to such changes. Adaptation and evolution of services are playing an important task in this domain. An essential issue to be addressed is how to efficiently select an adaptation while, there exists different strategies. We propose a fuzzy service adaptation approach that works based on the degree of QoS satisfaction. In particular, we define fuzzy parameters for the QoS property descriptions of Web Services. This way, partial satisfaction of parameters is allowed through measuring imprecise requirements. The QoS satisfaction degree is measured using membership functions provided for each parameter. Experimental results show the effectiveness of the fuzzy approach using the satisfaction degree in selecting the best adaptation strategy.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
