基于多元分层感知的移动物联网区域分割算法

为解决物联网区域分割引发的低质量数据传输、高频率网络拥塞等问题，提出一种基于多元分层感知机制的高效安全区域分割算法。根据节点间数据交换的紧密程度，将网络拓扑分割为网络层、传输层和最终汇聚层，设计多元分层感知模型，增强簇头节点的更新能力。结合机会路由连通特性，设计基于机会碰撞信息提取机制的区域分割子算法，借助拉格朗日模型进行特征挖掘，提升节点机会碰撞度并优化区域分割效果。基于簇内节点关联度，构建能量-路由双因子裁决机制，实现区域信息与簇头节点的数据交互并缓解数据拥塞。实验结果表明，与基于改进移动中继和楔形合并-能量空洞消除的区域分割算法相比，该算法具有更好的网络区域分割效果及更强的数据拥塞控制能力。

Region Segmentation Algorithm for Mobile Internet of Things Based on Multi-Layered Perception

To solve the problems of low data transmission quality and high-frequency congestion caused by region segmentation of Internet of Things(IoT), an efficient secure region segmentation algorithm based on multi-layered perception mechanism is proposed.Based on the tightness of data exchanges, the network topology is divided into network layer, transmission layer and final convergence layer.A network multi-layered perception model is designed to enhance the update ability of cluster head nodes.In view of the connectivity of opportunistic routing, a region segmentation sub-algorithm is designed based on the extraction mechanism for opportunistic collision information.The Lagrange method is used for feature mining to improve the opportunistic collision degree of nodes and to optimize region segmentation.Then based on the tightness of nodes within the cluster, a decision mechanism that considers both energy and routing is constructed to enable the data interactions between regional information and the cluster head node, and to alleviate data congestion.Experimental results show that the proposed algorithm has better network region segmentation performance and data congestion control ability than the region segmentation algorithms based on improved mobile relay or based on wedge merge-energy hole elimination, called MR and WM-EHP.