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QoS scheduling of fuzzy strategy grid workflow based on the bio-network

机译:基于生物网络的模糊策略网格工作流QoS调度

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摘要

Grid workflow may construct new value-added services by composing existing elementary services with sophisticated workflow logic. Grid workflow schedule requires sophisticated expertise of domain in order to automate the process of managing workflows and its components. Quality of service (QoS) becomes essential and poses great challenges to grid workflow. QoS-aware selection and execution of grid workflow can fulfil customer's expectations. A fuzzy strategy modelling approach is proposed to design the grid workflow schedule, which is inspired by the characteristics of emergence and self-evolution in biological immune system. The grid workflow matching relation is achieved by bio-entities (mobile agents) negotiation based on projection-join closure to capture such message situations. We propose a fuzzy preferences evolutionary algorithm to resolve the QoS-aware selection optimisation, which enables the construction of QoS-aware workflow at both abstract and concrete service levels. The simulation results show that the approach can significantly improve performance. It adapts well to the changes of environments.
机译:网格工作流可以通过将现有的基本服务与复杂的工作流逻辑进行组合来构造新的增值服务。网格工作流计划需要领域的专业知识,才能自动化管理工作流及其组件的过程。服务质量(QoS)变得至关重要,并且对网格工作流提出了巨大挑战。支持QoS的网格工作流选择和执行可以满足客户的期望。提出了一种模糊策略建模方法来设计网格工作流时间表,该方法受生物免疫系统出现和自我进化的特点启发。网格工作流匹配关系是通过基于投影联接闭合的生物实体(移动代理)协商来实现的,以捕获此类消息情况。我们提出了一种模糊偏好进化算法来解决QoS感知选择优化问题,该算法可以在抽象和具体服务级别上构建QoS感知工作流。仿真结果表明,该方法可以显着提高性能。它很好地适应环境的变化。

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