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Trust-Based and QoS Demand Clustering Analysis Customizable Cloud Workflow Scheduling Strategies

机译:基于信任的QoS需求聚类分析可定制的云工作流调度策略

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Due to the restrictions that most traditional scheduling strategies only care about users' QoS time or cost requirements, lack the effective analysis of users' real service demand and cannot guarantee scheduling security, this paper added trust intoworkflow's QoS target and proposed a novel customizable cloud workflow scheduling model. In order to better analyze differentuser's service requirements and provide customizable services, the new model divides workflow scheduling into two stages: the macro multi-workflow scheduling as the unit of cloud user and the micro single workflow scheduling. It introduced trust mechanism into multi-workflow scheduling level. And in single workflow scheduling level, it classified workflows into time sensitive, cost-sensitive and balance three types according to different workflow's QoS demand parameters using fuzzy clustering method. Basing on it, it customized different service strategies for different type. The simulation experiments show that the new schema has some advantages in shorteningworkflow's final completion time, achieving relatively high execution success rate and user satisfaction compared to other kindred solutions.
机译:由于大多数传统调度策略的局限性在于仅关注用户的QoS时间或成本需求,缺乏对用户真实服务需求的有效分析,无法保证调度的安全性,因此在工作流的QoS目标中增加了信任度,提出了一种新颖的可定制云工作流调度模型。为了更好地分析不同用户的服务需求并提供可定制的服务,新模型将工作流调度分为两个阶段:以云用户为单位的宏多工作流调度和微观单工作流调度。它将信任机制引入了多工作流调度级别。在单一工作流调度级别,采用模糊聚类方法,根据不同工作流的QoS需求参数,将工作流分为时间敏感型,成本敏感型和平衡型三种。在此基础上,针对不同类型定制了不同的服务策略。仿真实验表明,与其他同类解决方案相比,新方案在缩短工作流程的最终完成时间,实现较高的执行成功率和用户满意度方面具有优势。

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