QoS-based service selection is one of the important requirements in Service Oriented Computing (SOC). A challenging task towards this purpose is the selection of the best combination of services that fulfils user's requirements while meeting quality of service (QoS) constraints. This challenge becomes more complex when dealing with time-dependent QoS values and temporal properties. Indeed, during the selection, mutual dependencies between the different temporal constraints may arise so that the selection of each service may influence or be influenced by the selection of other services. On other side, to find the best solution, all potential combinations must be compared. However, the number of these combinations may be very high, which can present a barrier for enabling effective service selection. In this paper, we present a heuristic based timeaware service selection approach to efficiently select a close-tooptimal combination of services. First, pruning techniques are adopted to reduce the search space. Second, a novel heuristic approach is proposed based on service clustering, constraints decomposition and local selection while considering both QoS and temporal constraints. Finally, experiments which confirm the feasibility and effectiveness of the proposed approach in terms of its timeliness and optimality, are conducted.

Dynamic selection of the best services to execute abstract tasks of business processes is very important. Indeed, it enables to cope with complex user's requirements that require the collaboration of several more elementary services. However, with the increasing amount of candidate services of each business task that offer different QoS (Quality of Service) values, the selection of the optimal combination of services becomes a very hard task. This problem is more complex when dealing with temporal properties of business processes associated with time-dependent QoS parameters that can change according to the execution time. Unlike static QoS which have been deeply studied in the existing service selection approaches, time-dependent QoS are insufficiently taken into consideration. In this paper, we are interested in the problem of service selection to satisfy a given business process while considering temporal properties associated to time-dependent QoS. The selection approach that we propose relies on a new service pruning approach that is applied prior to our selection algorithm to reduce the number of candidate services while guaranteeing that the optimal solution still be found.

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.