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In this paper, we investigate the question of QoS prediction of Web Service Composition (WSC) implementing a business process. We focus on the graph reduction technique and the prediction of the Service Response Time. In the graph reduction technique, we assume that a Web Service Composition can be represented as a graph. The main thesis is that the QoS of(More)
In this work we study the portfolio problem which is to find a good combination of multiple heuristics to solve given instances on parallel resources in minimum time. The resources are assumed to be discrete, it is not possible to allocate a resource to more than one heuristic. Our goal is to minimize the average completion time of the set of instances,(More)
A challenging task in Web service composition is the runtime binding of a set of interconnected abstract services to concrete ones. This question, formulated as the service selection problem, has been studied in the area of service compositions implementing business processes. Despite the abundance of work on this topic, few of them match some practical(More)
The ever-increasing density in cloud computing parties, i.e. users, services, providers and data centres, has led to a significant exponential growth in: data produced and transferred among the cloud computing parties; network traffic; and the energy consumed by the cloud computing massive infrastructure, which is required to respond quickly and effectively(More)
Given a Web Services Composition, we deal with the prediction of the mean service response time that can be expected from a user request that is serviced. This challenge is a key issue in the design of middleware, managing Web Services Composition. We focus on complex services composition that can be described as BPMN choreographies of services. Our main(More)
The goal of this work is to study the portfolio problem which consists in finding a good combination of multiple heuristics given a set of a problem instances to solve. We are interested in a parallel context where the resources are assumed to be discrete and homogeneous, and where it is not possible to allocate a same resource to more than one heuristic.(More)
We propose a new mixed integer linear programming approach to solve the classical problem of scheduling independent parallel tasks without preemption. We propose a formulation where the goal is to minimize the makespan.Then we show the flexibility of this approach by extending the result to the contiguous case. We validate this approach with some(More)
Traditional automatic tuning systems are based on an exploration-exploitation tradeoff that consists of: learning the behavior of the algorithm to tune on several benchmarks (exploration) and then using the learned behavior for solving new problem instances. On NP-hard algorithms, this vision is questionable because of the potential huge runtime of the(More)