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Offline and online power aware resource allocation algorithms with migration and delay constraints

机译:具有迁移和延迟约束的离线和在线功率感知资源分配算法

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In order to handle advanced mobile broadband services and Internet of Things (IoT), future Internet and 5G networks are expected to leverage the use of network virtualization, be much faster, have greater capacities, provide lower latencies, and significantly be power efficient than current mobile technologies. Therefore, this paper proposes three power aware algorithms for offline, online, and migration applications, solving the resource allocation problem within the frameworks of network function virtualization (NFV) environments in fractions of a second. The proposed algorithms target minimizing the total costs and power consumptions in the physical network through sufficiently allocating the least physical resources to host the demands of the virtual network services, and put into saving mode all other not utilized physical components. Simulations and evaluations of the offline algorithm compared to the state of-art resulted on lower total costs by 32%. In addition to that, the online algorithm was tested through four different experiments, and the results argued that the overall power consumption of the physical network was highly dependent on the demands' lifetimes, and the strictness of the required end-to-end delay. Regarding migrations during online, the results concluded that the proposed algorithms would be most effective when applied for maintenance and emergency conditions. (C) 2019 Elsevier B.V. All rights reserved.
机译:为了处理先进的移动宽带服务和物联网(物联网),预计未来的互联网和5G网络将利用网络虚拟化的使用,更快,具有更大的容量,提供更低的延迟,并显着低于当前功率效率移动技术。因此,本文提出了三个用于脱机,在线和迁移应用程序的动力感知算法,在一秒的分数中解决网络功能虚拟化(NFV)环境中的资源分配问题。所提出的算法目标通过充分地分配最不分配的物理资源来最大限度地减少物理网络中的总成本和功耗,以托管虚拟网络服务的需求,并投入保存模式所有不使用物理组件。与现有技术相比的离线算法的仿真和评估导致总成本较低32%。除此之外,在线算法通过四种不同的实验测试,结果表明,物理网络的总功率消耗高度依赖于需求的寿命,以及所需的端到端延迟的严格性。关于在线期间的迁移,结果得出结论认为,当申请维护和紧急情况时,所提出的算法将是最有效的。 (c)2019 Elsevier B.v.保留所有权利。

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