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A Dynamic QoS-Aware Logistics Service Composition Algorithm Based on Social Network

机译:基于社交网络的动态QoS感知物流服务组合算法

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The public logistics platform aims to provide customers with end-to-end logistics services by finding and composing a huge quantity of web services from logistics service providers. But, traditional service composition required predefined business process so that its flexibility is far from satisfactory in the problem. Path planning can be a solution of finding a suitable business path during service composition, but the search space will increase dramatically with the growth of service quantity and is hard to get a result within a tolerable interaction time. In the context of big data, to quickly build a service path with the optimal global QoS has become a problem demanding prompt solution. Sociologists point out that companies prefer familiar partners in the commercial environment. Using this principle, a concept of partner circle is defined, which can significantly reduce the search space in path planning. Combining path planning with service composition, a PartnerFirst algorithm is presented based on the social network, which is the cooperation network of service providers here. Simulation experiment shows that the PartnerFirst algorithm outperforms current approaches over 10 times in efficiency, with just about 10% loss in QoS. The relationship between efficiency and service quantity of the PartnerFirst algorithm is nearly linear. It proves that using social network in dynamic service composition is efficient and effective.
机译:该公共物流平台旨在通过查找和组合来自物流服务提供商的大量Web服务,为客户提供端到端的物流服务。但是,传统的服务组合需要预定义的业务流程,因此其灵活性远远不能令人满意。路径规划可以是在服务组合期间找到合适的业务路径的解决方案,但是搜索空间将随着服务数量的增加而急剧增加,并且在可容忍的交互时间内很难获得结果。在大数据的情况下,快速构建具有最佳全局QoS的服务路径已成为要求迅速解决的问题。社会学家指出,公司在商业环境中更喜欢熟悉的合作伙伴。使用此原理,定义了伙伴圆的概念,可以大大减少路径规划中的搜索空间。将路径规划与服务组合相结合,提出了一种基于社交网络的PartnerFirst算法,该社交网络是此处服务提供商的合作网络。仿真实验表明,PartnerFirst算法的效率比现有方法高出10倍以上,而QoS损失仅为10%。 PartnerFirst算法的效率和服务数量之间的关系几乎是线性的。证明了在动态服务组合中使用社交网络是有效的。

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