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A two-level cooperative clustering scheme for vehicular communications

机译:一种用于车辆通信的两级合作聚类方案

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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:本文提出了一种用于车辆通信的两级合作网络方案。网络架构在一组基于网络中的节点密度的一组部署的路边单元(RSU)上组成,而这些节点被组织为车辆ad-hoc网络。使用K-Means算法以及GAP统计量以及获得最佳基站的最佳数量来获得RSU的位置。基于每个节点的地理位置和动态,通过与环境的可预测和高度相关的行为来聚类节点。使用联合游戏的概念选择头部群集以扩展群集的稳定性。另外,使用头簇发送的信标在RSU中,实现了集群节点的动态行为的预测。 RSU使用LTE链路互连以提供协作方案,授予头部集群的最佳选择,并延长其寿命。最后,分析了所提出的两级网络方案以及群集预测方法,并与实际情况中的常用聚类技术进行比较。仿真结果表明,合作方案开发的积极影响预测簇的运动。

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