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An Effective Dynamic Web Service Selection Strategy with Global Optimal QoS Based on Particle Swarm Optimization Algorithm

机译:基于粒子群优化算法的全局最优QoS动态Web服务选择策略

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Dynamic Web service selection with global QoS optimization in Web service composition is a critical issue in Web service composition. In order to solve the problem, based on intelligent optimal theory of particle swarm optimization (PSO) algorithm, we propose a strategy PSO-GODSS (global optimization of dynamic Web service selection based on PSO) algorithm to implement Web service selection with QoS global optimization. The basic idea of the algorithm is to transform the original Web service selection problem into a multi-objective services composition optimization problem with global QoS constraints, which is further transformed into a single-objective problem by using the method of ideal point. Then, the theory of intelligent optimization of PSO is applied to produce a set of optimal services composition process with QoS constraints. Theoretical analysis and experimental results indicate the feasibility and efficiency of this algorithm, and the execution efficiency and convergence rate of PSO-GODSS are much better than that of multi-objective genetic algorithm used in prior work.
机译:Web服务组合中具有全局QoS优化的动态Web服务选择是Web服务组合中的关键问题。为了解决该问题,基于粒子群优化(PSO)算法的智能优化理论,提出了一种策略PSO-GODSS(基于PSO的动态Web服务选择的全局优化)算法,用于实现QoS全局优化的Web服务选择。 。该算法的基本思想是将原始的Web服务选择问题转化为具有全局QoS约束的多目标服务组合优化问题,并通过理想点方法将其进一步转化为单目标问题。然后,运用PSO的智能优化理论,产生了一组具有QoS约束的最优服务组合过程。理论分析和实验结果表明了该算法的可行性和有效性,PSO-GODSS的执行效率和收敛速度远远优于先前工作中使用的多目标遗传算法。

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