Mobile edge computing and network function virtualization (NFV) paradigms enable new flexibility and possibilities of the deployment of extreme low-latency services for Internet-of-Things (IoT) applications within the proximity of their users. However, this poses great challenges to find optimal placements of virtualized network functions (VNFs) for data processing requests of IoT applications in a multi-tier cloud network, which consists of many small- or medium-scale servers, clusters, or cloudlets deployed within the proximity of IoT nodes and a few large-scale remote data centers with abundant computing and storage resources. In particular, it is challenging to jointly consider VNF instance placement and routing traffic path planning for user requests, as they are not only delay sensitive but also resource hungry. In this article, we consider admissions of NFV-enabled requests of IoT applications in a multi-tier cloud network, where users request network services by issuing service requests with service chain requirements, and the service chain enforces the data traffic of the request to pass through the VNFs in the chain one by one until it reaches its destination. To this end, we first formulate the throughput maximization problem with the aim to maximize the system throughput. We then propose an integer linear program solution if the problem size is small; otherwise, we devise an efficient heuristic that jointly takes into account VNF placements to both cloudlets and data centers and routing path finding for each request. For a special case of the problem with a set of service chains, we propose an approximation algorithm with a provable approximation ratio. Next, we also devise efficient learning-based heuristics for VNF provisioning for IoT applications by incorporating the mobility and energy conservation features of IoT devices. We finally evaluate the performance of the proposed algorithms by simulations. The simulation results show that the performance of the proposed algorithms is promising.

中文翻译：

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用于多层移动边缘网络中物联网应用的 QoS 感知 VNF 放置和服务链

移动边缘计算和网络功能虚拟化 (NFV) 范式为在用户附近的物联网 (IoT) 应用程序部署极低延迟服务提供了新的灵活性和可能性。然而，这对在多层云网络中为物联网应用程序的数据处理请求找到虚拟化网络功能 (VNF) 的最佳位置提出了巨大挑战，该网络由部署在其中的许多中小型服务器、集群或小云组成。靠近物联网节点和一些具有丰富计算和存储资源的大型远程数据中心。特别是，为用户请求联合考虑 VNF 实例放置和路由流量路径规划具有挑战性，因为它们不仅对延迟敏感，而且资源匮乏。在本文中，我们考虑在多层云网络中允许物联网应用程序的NFV启用请求，其中用户通过发出具有服务链要求的服务请求来请求网络服务，并且服务链强制请求的数据流量通过VNF。链子一个接一个，直到它到达目的地。为此，我们首先制定吞吐量最大化问题，以最大化系统吞吐量。然后，如果问题规模很小，我们会提出一个整数线性规划解决方案；否则，我们设计了一种有效的启发式方法，该方法将 VNF 放置到小云和数据中心以及每个请求的路由路径查找共同考虑在内。对于一组服务链问题的特殊情况，我们提出了一种具有可证明近似比的近似算法。下一个，我们还通过结合物联网设备的移动性和节能特性，为物联网应用程序的 VNF 配置设计了有效的基于学习的启发式方法。我们最终通过模拟评估了所提出算法的性能。仿真结果表明，所提算法的性能是有希望的。