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Towards the optimality of QoS-aware web service composition with uncertainty

机译:在不确定的情况下实现可感知QoS的Web服务组合的最优性

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摘要

Quality of service (QoS)-aware web service composition (QWSC) has recently become one of the most challenging research issues. Although much work has been investigated, they mainly focus on certain QoS of web services, while QoS with uncertainty exposes the most important characteristic in real and highly dynamic environment. In this paper, with the consideration of uncertain service QoS and user's preferences, we model the issue of uncertain QoS-aware WSC via interval number and translate it into a multi-objective optimisation problem with global QoS constraints of user's preferences. The encoded optimisation problem is solved by an non-deterministic multi-objective evolutionary algorithm, which exploits new genetic encoding schema, the strategy of crossover and uncertain interval Pareto comparison. To validate the feasibility, large-scale experiments have been conducted on simulated datasets. The results demonstrate that our proposed approach can effectively and efficiently find optimum composite service solutions set with satisfactory convergence.
机译:支持服务质量(QoS)的Web服务组合(QWSC)最近已成为最具挑战性的研究问题之一。尽管已经进行了大量研究,但它们主要集中在Web服务的某些QoS上,而具有不确定性的QoS则暴露了在真实且高度动态的环境中的最重要特征。本文在考虑不确定服务QoS和用户偏好的情况下,通过区间数对不确定QoS感知的WSC问题进行建模,并将其转化为具有用户偏好全局QoS约束的多目标优化问题。通过一种不确定的多目标进化算法解决了编码优化问题,该算法利用了新的遗传编码方案,交叉策略和不确定区间帕累托比较。为了验证可行性,已对模拟数据集进行了大规模实验。结果表明,我们提出的方法可以有效,高效地找到具有令人满意的收敛性的最佳组合服务解决方案。

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