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A two-level cooperative clustering scheme for vehicular communications

机译:车载通信的两级协作聚类方案

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A two-level cooperative network scheme for vehicular communications is proposed in this paper. The network architecture consists on a set of deployed RoadSide Units (RSU) based on the expected density of nodes in the network whereas these nodes are organized as a vehicular ad-hoc network. The position of the RSUs is obtained using the k-means algorithm along with the gap statistic to obtain the optimal number of base stations. The nodes are clustered using spectral clustering based on the geographical position and dynamics of each node, subject to their predictable and highly correlated behavior with the environment. The head-cluster is chosen using concepts of coalitional games in order to extend the stability of the cluster. Additionally, using the beacons sent by the head-cluster to the RSU, a prediction in the dynamic behavior of the clustered nodes is achieved. The RSUs are interconnected using LTE links to provide a cooperative scheme, granting an optimal selection of the head-cluster, and prolonging its lifetime. Finally, the proposed two-level network scheme along with the clustering prediction method are analyzed and compared with the commonly used clustering techniques in a real scenario. The simulation results show the positive impact of the cooperative scheme developed predicting the movement of the clusters.
机译:提出了一种用于车辆通信的两级协作网络方案。网络体系结构基于网络中节点的预期密度,由一组已部署的RoadSide Units(RSU)组成,而这些节点被组织为车辆自组织网络。 RSU的位置是使用k-means算法以及间隙统计量获得的,以获得最佳基站数量。根据每个节点的地理位置和动态,使用光谱聚类对节点进行聚类,取决于它们与环境的可预测和高度相关的行为。使用联盟博弈的概念选择头集群,以扩展集群的稳定性。此外,使用头簇发送给RSU的信标,可以预测群集节点的动态行为。 RSU使用LTE链路互连,以提供一种协作方案,允许对头簇进行最佳选择,并延长其使用寿命。最后,对提出的二级网络方案以及聚类预测方法进行了分析,并与实际场景中常用的聚类技术进行了比较。仿真结果表明,所开发的预测集群运动的协作方案具有积极的影响。

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