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BULLET: Particle Swarm Optimization Based Scheduling Technique for Provisioned Cloud Resources

机译:子弹:基于粒子群优化的预配置云资源调度技术

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Cloud resource scheduling requires mapping of cloud resources to cloud workloads. Scheduling results can be optimized by considering Quality of Service (QoS) parameters as inherent requirements of scheduling. In existing literature, only a few resource scheduling algorithms have considered cost and execution time constraints but efficient scheduling requires better optimization of QoS parameters. The main aim of this research paper is to present an efficient strategy for execution of workloads on cloud resources. A particle swarm optimization based resource scheduling technique has been designed named as BULLET which is used to execute workloads effectively on available resources. Performance of the proposed technique has been evaluated in cloud environment. The experimental results show that the proposed technique efficiently reduces execution cost, time and energy consumption along with other QoS parameters.
机译:云资源调度需要将云资源映射到云工作负载。通过将服务质量(QoS)参数视为调度的内在要求,可以优化调度结果。在现有文献中,只有少数资源调度算法考虑了成本和执行时间限制,但是有效的调度需要对QoS参数进行更好的优化。本研究论文的主要目的是提出一种有效的策略,用于在云资源上执行工作负载。已经设计了一种基于粒子群优化的资源调度技术,称为BULLET,用于在可用资源上有效执行工作负载。所提出技术的性能已在云环境中进行了评估。实验结果表明,该技术有效降低了执行成本,时间和能耗以及其他QoS参数。

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