Wu Xing, Duan Jing, Zhong Mingyu, Li Peng, Wang Jianjia
School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China.
Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai 200444, China.
Sensors (Basel). 2020 Jul 8;20(14):3819. doi: 10.3390/s20143819.
With the advent of the Internet of things (IoT), intelligent transportation has evolved over time to improve traffic safety and efficiency as well as to reduce congestion and environmental pollution. However, there are some challenging issues to be addressed so that it can be implemented to its full potential. The major challenge in intelligent transportation is that vehicles and pedestrians, as the main types of edge nodes in IoT infrastructure, are on the constant move. Hence, the topology of the large scale network is changing rapidly over time and the service chain may need reestablishment frequently. Existing Virtual Network Function (VNF) chain placement methods are mostly good at static network topology and any evolvement of the network requires global computation, which leads to the inefficiency in computing and the waste of resources. Mapping the network topology to a graph, we propose a novel VNF placement method called BVCP (Border VNF Chain Placement) to address this problem by elaborately dividing the graph into multiple subgraphs and fully exploiting border hypervisors. Experimental results show that BVCP outperforms the state-of-the-art method in VNF chain placement, which is highly efficient in large scale IoT of intelligent transportation.
随着物联网（IoT）的出现，智能交通不断发展，以提高交通安全和效率，减少拥堵和环境污染。然而，仍有一些具有挑战性的问题需要解决，以便充分发挥其潜力。智能交通的主要挑战在于，作为物联网基础设施中主要边缘节点类型的车辆和行人处于不断移动的状态。因此，大规模网络的拓扑结构随时间快速变化，服务链可能需要频繁重新建立。现有的虚拟网络功能（VNF）链放置方法大多适用于静态网络拓扑，网络的任何演变都需要进行全局计算，这导致计算效率低下和资源浪费。通过将网络拓扑映射到图上，我们提出了一种名为BVCP（边界VNF链放置）的新型VNF放置方法，通过精心将图划分为多个子图并充分利用边界管理程序来解决此问题。实验结果表明，BVCP在VNF链放置方面优于现有方法，在大规模智能交通物联网中具有很高的效率。
