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Energy-Aware Distributed Multi-Cloud Flower Pollination Optimization Scheme

机译:节能分布式多云花授粉优化方案

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Cloud computing has rapidly emerged as a successful paradigm for providing ICT infrastructure, resources, and services on a pay-per-use basis over the past few years. The wider adoption of Cloud and virtualization technologies has led to the establishment of large-scale datacenters that consume excessive energy. This paper proposed Energy-Aware distributed MultiCloud Flower Pollination Optimization (EAdM-FPO) scheme for minimizing energy consumption and SLA violation with higher resource utilization in a distributed datacenters that belong to a single service provider located in different environments using centralized architecture. The proposed scheme overcome the limitation of using single Cloud datacenter. Four mechanisms namely; Dynamic Switching Probability (DSP), Power Usage Effectiveness (PUE), clustering, and migration controller have been incorporated into the EAdM-FPO scheme to further improve resource management and to reduce the computational complexity of the original FPA. EAdM-FPO scheme has been evaluated based on average energy consumption, VM migration, and SLA violation. In addition, the performance of the proposed EAdM-FPO scheme has been evaluated and compared with related existing schemes based on the same metrics and configuration. Thus, the EAdM-FPO scheme significantly reduce the energy consumption and increase the datacenter resource utilization with less Service Level Agreement (SLA) violation.
机译:在过去的几年中,云计算已迅速成为一种成功的范例,可以按使用量付费提供ICT基础设施,资源和服务。云和虚拟化技术的广泛采用已导致建立消耗大量能源的大型数据中心。本文提出了一种能源感知分布式多云花授粉优化(EAdM-FPO)方案,该方案可通过使用集中式架构在属于不同环境中的单个服务提供商的分布式数据中心中以更高的资源利用率来最大程度地减少能耗和SLA违规。所提出的方案克服了使用单个云数据中心的局限性。四种机制分别是: EAdM-FPO方案中已合并了动态交换概率(DSP),电源使用效率(PUE),群集和迁移控制器,以进一步改善资源管理并降低原始FPA的计算复杂性。 EAdM-FPO方案已根据平均能耗,VM迁移和违反SLA进行了评估。此外,已经基于相同的度量和配置对提议的EAdM-FPO方案的性能进行了评估,并将其与相关的现有方案进行了比较。因此,EAdM-FPO方案显着减少了能耗,并以更少的服务水平协议(SLA)违反提高了数据中心资源的利用率。

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