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Multidimensional QoS Resource Scheduling Method with Stakeholder Perspective in Clouds

机译:利益相关者视角的云中多维QoS资源调度方法

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Cloud computing environment is complex and changeable. It needs to implement the application of large-scale, dynamic, and indefinite cloud users in the form of cloud tasks to a cloud resource environment with physical location separation, heterogeneous resources, and multiple constraints. In order to solve the resource scheduling problem of cloud computing, this paper meets the QoS requirements of cloud users and cloud computing service providers from multiple dimensions, and realizes ultra-large-scale, high-performance and energy-efficient cloud computing resource scheduling. In this paper, a multidimensional QoS cloud computing resource scheduling method with stakeholder perspective of cloud users and cloud computing service providers is implemented, which includes proposing a 2-level cloud computing resource scheduling structure, constructing a multidimensional QoS cloud computing resource scheduling model, designing an MQoS cloud computing resource scheduling optimization algorithm, and simultaneously optimizing multiple objective functions. Performance analysis show that MQoS has obvious advantages in multidimensional QoS performance compared with FIFO algorithm and Genetic algorithm, and achieves good cloud computing system utility to meet the interests of cloud users and cloud computing service providers. MQoS algorithm is also far superior to the traditional algorithms in cloud data center load balancing difference.
机译:云计算环境复杂多变。它需要以云任务的形式,将大规模,动态和不确定的云用户应用到具有物理位置分离,异构资源和多个约束的云资源环境中。为了解决云计算的资源调度问题,本文从多方面满足了云用户和云计算服务提供商的QoS要求,实现了超大规模,高性能,高能效的云计算资源调度。本文从云用户和云计算服务提供商的利益相关者角度出发,实现了一种多维QoS云计算资源调度方法,该方法包括提出一种二级云计算资源调度结构,构建多维QoS云计算资源调度模型,进行设计。一种MQoS云计算资源调度优化算法,同时优化多个目标函数。性能分析表明,与FIFO算法和遗传算法相比,MQoS在多维QoS性能上具有明显的优势,并具有良好的云计算系统实用性,可以满足云用户和云计算服务提供商的利益。在云数据中心负载均衡方面,MQoS算法也远远优于传统算法。

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