In service-oriented environments, abstract business processes can be implemented by concrete services to build complex applications. Given global user constraints, service selection allows to identify the best combination of services with respect to the business constraints. Generally, the selection problem is challenging, but it is particularly complex when dealing with QoS (quality of service) values, which can change during the time associated with temporal constraints. Indeed, these constraints make the selection problem heavily constrained, which can present a barrier for enabling effective service selection. Unlike static QoS values which have been deeply studied in the existing service selection approaches, time-dependent QoS associated with temporal constraints are insufficiently taken into consideration. Moreover, existing approaches cannot handle heavily constrained problems and usually do not provide strategies to detect the source of failure in order to enhance the selection problem in case there is no solution. In this paper, we introduce a new service selection approach, while considering time-dependent QoS values associated with temporal constraints. First, pruning techniques are proposed. The aim of the pruning process is twofold: (1) it allows for reducing the search space and thus, enhancing the efficiency of the selection process; (2) it allows for improving the selection problem by detecting at earlier stages the possible causes of failure, even before the selection process. Second, based on the pruning phase, improvement techniques are proposed to identify possible actions for finding a solution. Third, an exact and an approximate service selection algorithms under several constraints are given. Finally, we demonstrate the effectiveness of our approach through experimental results.

中文翻译：

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基于剪枝和改进技术的服务组合时间感知选择方法

在面向服务的环境中，抽象的业务流程可以通过具体的服务来实现，以构建复杂的应用程序。给定全局用户约束，服务选择允许根据业务约束识别服务的最佳组合。通常，选择问题具有挑战性，但在处理 QoS（服务质量）值时尤其复杂，QoS（服务质量）值会在与时间约束相关的时间内发生变化。事实上，这些约束使选择问题受到严重限制，这可能成为实现有效服务选择的障碍。与在现有服务选择方法中已经深入研究的静态 QoS 值不同，与时间约束相关的时间相关 QoS 没有得到充分考虑。而且，现有方法无法处理严重受限的问题，并且通常不提供检测失败来源的策略，以便在没有解决方案的情况下增强选择问题。在本文中，我们介绍了一种新的服务选择方法，同时考虑了与时间约束相关的时间相关 QoS 值。首先，提出了修剪技术。修剪过程的目的有两个：（1）它允许减少搜索空间，从而提高选择过程的效率；(2) 它允许通过在早期阶段甚至在选择过程之前检测可能的失败原因来改进选择问题。其次，基于修剪阶段，提出了改进技术来确定寻找解决方案的可能操作。第三，给出了几种约束条件下的精确和近似服务选择算法。最后，我们通过实验结果证明了我们方法的有效性。