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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耗意识资源分配算法

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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（IoT），预计未来的Internet和5G网络将利用网络虚拟化的优势，速度要快得多，容量更大，等待时间更短，并且在能源效率上要比目前高得多。移动技术。因此，本文提出了三种针对脱机，在线和迁移应用程序的功耗感知算法，可在不到一秒钟的时间内解决网络功能虚拟化（NFV）环境框架内的资源分配问题。所提出的算法旨在通过充分分配最少的物理资源来承载虚拟网络服务的需求，从而使物理网络中的总成本和功耗最小化，并将所有其他未使用的物理组件置于保存模式。与现有技术相比，离线算法的仿真和评估可将总成本降低32％。除此之外，还通过四个不同的实验对在线算法进行了测试，结果表明，物理网络的总体功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，提出的算法在应用于维护和紧急情况时将是最有效的。 （C）2019 Elsevier B.V.保留所有权利。

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