Time-Dependent QoS Aware Best Service Combination Selection

Abstract

Service Oriented Architecture allows developing complex business applications from existing services. Given that many services are available with the same functionality and with different Quality of Service (QoS) attributes, one common challenge is to select the best service combination regarding user's requirements. Existing solutions often consider static QoS values for candidate services. Nevertheless, in real world applications, QoS values can change during time. In addition, besides structural constraints, several QoS and temporal constraints can also be specified at the business level. Considering time-dependent QoS values associated with business level constraints makes the selection process a very complex and time consuming decision problem given the large number of service combinations to be compared. To deal with this issue, in this paper, the authors propose a novel service selection approach based on QoS and temporal pruning techniques to reduce the number of candidate services. The proposed approach allows pruning uninteresting services based on a set of local thresholds. These latter are measured using constraint optimization models while dealing with general flow structures including sequential, parallel, choice and loop patterns and different types of QoS and temporal constraints. Experimental studies show the benefits of the proposed approach in particular in terms of computational time.