Online VNF Placement and Chaining for Value-added Services in Content Delivery Networks

N. T. Jahromi, Somayeh Kianpisheh, R. Glitho
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引用次数: 21

Abstract

Value-added Services (VASs) (e.g. dynamic site acceleration, media management) play a critical role in Content Delivery Networks (CDNs). Network Functions Virtualization (NFV) enables the agile provisioning of VASs. In NFV settings, VASs are provisioned as ordered sets of Virtual Network Functions (VNFs), forming VNF-Forwarding Graphs (VNF-FG) which are deployed in the CDN infrastructure. The CDN VAS VNF-FGs have a specific characteristic: they have one end-point (corresponding to the content server) that is unknown, prior to their placement. The proposals for CDN VAS VNF-FG placement, so far, have only considered offline placement, where the VNF-FGs are placed before end-user traffic steers into the network. However, in concrete cases, a change in service usage patterns might occur, a situation that could require a VNF-FG placement in an online manner. This paper tackles the problem of online VNF-FG placement for VASs in CDNs, taking into account the eventual reuses and migrations of already-deployed VNFs. A cost model is considered, including multiple costs; i.e. new VNF instantiations, migration, hosting and routing costs. The objective is to optimally place the VNF-FGs such that total reconfiguration costs are minimized while QoS is satisfied. An Integer Linear Programming (ILP) formulation is provided and evaluated in a small-scale scenario.
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内容交付网络中增值业务的在线VNF放置和链接
增值服务(VASs)(如动态站点加速、媒体管理)在内容分发网络(cdn)中起着关键作用。网络功能虚拟化(Network Functions Virtualization, NFV)实现了虚拟网关的敏捷发放。在NFV环境中,VASs作为有序的VNFs (Virtual Network Functions)集合发放,形成VNF-Forwarding Graphs (VNF-FG),部署在CDN基础设施中。CDN VAS vnf - fg有一个特定的特征:它们在放置之前有一个未知的端点(对应于内容服务器)。到目前为止,关于CDN VAS VNF-FG放置的建议只考虑了离线放置,其中VNF-FG放置在最终用户流量转向网络之前。但是,在具体情况下,可能会发生服务使用模式的变化,这种情况可能需要以在线方式放置VNF-FG。本文解决了cdn中VASs的在线VNF-FG放置问题,并考虑了已部署vnf的最终重用和迁移。考虑一个成本模型,包括多个成本;例如,新的VNF实例化、迁移、托管和路由成本。目标是最优地放置vnf - fg,以便在满足QoS的同时最小化总重新配置成本。给出了一个整数线性规划(ILP)公式,并在一个小规模的场景中进行了评估。
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