支持5G的城市车辆网络中的边缘节点放置:基于中心性的方法

Moyukh Laha, Suraj Kamble, R. Datta
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引用次数: 7

摘要

智能城市的下一代车辆应用,包括辅助自动驾驶,需要复杂的数据处理和快速的信息交换。解决这些需求的实用方法是采用5G架构中的边缘计算范式,将存储、计算和网络资源带到网络边缘,即更靠近最终用户。边缘节点(EN)在地理上覆盖在一个地区,因此,车辆应用的有效性与这些节点的正确放置直接相关。然而,在路边部署边缘节点提出了成本效益的挑战。在本文中,我们讨论了在有限预算的城市场景下,有限数量的边缘节点的有效部署。为此,我们使用基于复杂网络的中心性度量和车辆交通分布来综合考虑路网的结构特性,对边缘节点放置的候选站点进行排序。在此基础上,将边缘节点部署问题表述为一个典型的NP问题——0-1背包问题,并给出了基于动态规划的求解方法。我们在真实交通的城市场景中评估了所提出的方法,并提供了确凿的证据,证明我们提出的方案对所定义的问题产生了实际的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Edge Nodes Placement in 5G enabled Urban Vehicular Networks: A Centrality-based Approach
The next generation vehicular applications in smart cities, including aided self-driving, require intricate data processing and quick message exchanges. A pragmatic approach to address these requirements is to adopt the edge-computing paradigm from 5G architecture, where storage, computing, and networking resources are brought to the edge of the network, i.e., closer to the end-users. Edge nodes (EN) are geographically overlaid across a region, and therefore, the effectiveness of the vehicular applications is directly associated with the proper placement of such nodes. However, the deployment of edge nodes on the roadsides presents a challenge of cost-effectiveness. In this paper, we address the efficient deployment of a limited number of edge nodes in an urban scenario under a restricted budget. To this end, we jointly consider the structural properties of the road network using complex-network based centrality metrics and the vehicular traffic distribution to rank the candidate sites for edge node placement. Thereafter, we formulate the problem of edge node deployment as a 0–1 knapsack problem, which is a classical NP problem and provide a dynamic programming based solution to it. We evaluate the proposed method in an urban scenario with real traffic and present conclusive proof that our proposed scheme yields a practical solution to the defined problem.
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