5g边缘计算环境中动态和移动性感知的VNF放置

J. Vieira, A. L. E. Battisti, E. Macedo, Paulo F. Pires, D. Muchaluat-Saade, Flávia Coimbra Delicato, A. Oliveira
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引用次数: 2

摘要

网络功能虚拟化(NFV)和边缘计算的结合,通过利用边缘设备和用户的接近性,促进了延迟严格应用的服务质量(QoS)的实现,并提供了必要的灵活性,为5G环境实现敏捷、经济高效和按需服务交付模型。但是,为了实现这些优势,必须部署VNFs,以优化系统资源利用率并保持业务QoS。在这种情况下,选择最合适的边缘节点来部署VNF是一个具有挑战性的研究问题,因为VNF放置算法必须考虑多个(通常是相互冲突的)目标。当考虑到边缘环境的高动态时,挑战变得更大。边缘节点和用户位置的可用性随着时间的推移而变化,使得原始的分配决策无效。在本文中,我们提出了DSP,一种考虑5G边缘环境动态特性的动态智能VNF放置算法。我们的建议侧重于通过在线放置方法来优化资源利用,以处理不断到达的服务请求。此外,我们还考虑了用户的移动性,提供了一种减少用户移动造成的性能影响的方法。此外,还提供了两级资源共享机制,将基础设施提供商的成本降至最低,同时对QoS的影响很小。
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Dynamic and Mobility-Aware VNF Placement in 5G-Edge Computing Environments
The combination of both Network Function Virtualization (NFV) and Edge Computing facilitates the Quality of Service (QoS) fulfillment of latency-stringent applications by taking advantage of the proximity of the devices at the edge and the user, and provides the necessary flexibility to enable agile, cost-effective, and on-demand service delivery models for 5G environments. However, to achieve those benefits, VNFs must be deployed so that system resource utilization is optimized and service QoS is maintained. In this context, the selection of the most suitable edge nodes to deploy VNFs is a challenging research issue because multiple — and often conflicting — objectives must be considered by the VNF placement algorithm. The challenges become greater when considering the high dynamism of the edge environment. The availability of edge nodes and users’ locations vary over time, making original allocation decisions ineffective. In this paper, we propose DSP, a Dynamic Smart VNF Placement algorithm that considers the dynamic nature of a 5G edge environment. Our proposal focuses on optimizing resource utilization with an online placement approach to handle continuously arriving service requests. Furthermore, we also account for user mobility providing an approach that reduces the performance impact caused by users’ movement. Additionally, a two-level resource-sharing mechanism is provided, minimizing the cost for the infrastructure provider with low impact on QoS.
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