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An Efficient Web Service Composition Approach Based on improved Particle Swarm Optimization Model

机译：基于改进粒子群优化模型的高效网络服务组合方法

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Along with the rapid growth of the number of the available web services over the internet, the quality of services (Qos) becomes an imperative concern for service consumers and providers. How to differentiate their quality based on Qos criteria at web service level is a challenging issue. Considering that evolutionary algorithm has powerful ability of searching information, a new web service composition model under improved particle swarm optimization (IPSO) algorithm is presented in this paper. According to the non-functional attributes Qos of services, the model can select web services with optimal Qos and compose them into value-added web services. Furthermore, IPSO model not only can find the service with optimal Qos immediately but also can overcome the bottleneck of the standard PSO model. It can balance the exploitation and exploration and avoid premature convergence to some extent. As a result, web services can be invocated dynamically and be composed automatically and efficiently. The preliminary experimental results indicate that the web service composition approach based on IPSO model is applicable and feasible to the optimization of general service compositions.
机译：随着互联网上可用Web服务数量的快速增长，服务质量（QoS）成为服务消费者和提供商的必要性。如何根据Web服务级别的QoS标准区分其质量是一个具有挑战性的问题。考虑到进化算法具有搜索信息的强大能力，本文介绍了改进粒子群优化（IPSO）算法下的新的Web服务成分模型。根据非功能性属性的服务QoS，该模型可以选择具有最佳QoS的Web服务，并将它们撰写为增值Web服务。此外，IPSO模型不仅可以立即找到具有最佳QoS的服务，还可以克服标准PSO模型的瓶颈。它可以在一定程度上平衡开发和探索，避免过早收敛。因此，可以动态调用Web服务，并自动和有效地进行调用。初步实验结果表明，基于IPSO模型的Web服务组合方法适用，可行的通用服务组合物的优化。

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