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Efficient Heuristic Approach with Improved Time Complexity for Qos-Aware Service Composition

机译:Qos感知服务组合的有效启发式方法和改进的时间复杂度

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Service-Oriented Architecture enables the composition of loosely coupled services provided with varying Quality of Service (QoS) levels. Given a composition, finding the set of services that optimizes some QoS attributes under given QoS constraints has been shown to be NP-hard. Therefore, heuristic algorithms are widely used, finding acceptable solutions in polynomial time. Still the time complexity of such algorithms can be prohibitive for real-time use, especially if the algorithms are required to run until they find near-optimal solutions. Thus, we propose a heuristic approach based on Hill-Climbing that makes effective use of an initial bias computed with Linear Programming, and works on a reduced search space. In our evaluation, we show that our approach finds near-optimal solutions and achieves a low time complexity.
机译:面向服务的体系结构可实现具有变化的服务质量(QoS)级别的松散耦合服务的组合。给定组成,找到在给定QoS约束下优化某些QoS属性的服务集已被证明是NP难的。因此,启发式算法被广泛使用,在多项式时间内找到可接受的解。这样的算法的时间复杂度仍然不能用于实时使用,特别是如果算法需要运行直到找到接近最佳的解决方案时尤其如此。因此,我们提出了一种基于Hill-Climbing的启发式方法,该方法有效利用了通过线性规划计算出的初始偏差,并在缩小的搜索空间上工作。在我们的评估中,我们证明了我们的方法找到了近乎最佳的解决方案,并实现了较低的时间复杂度。

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