面向IPv6物联子网的轻量级树型转发模型

在IPv6 物联网中，RPL 路由模型已得到广泛的认可.然而对于规模较大的多跳网络结构，RPL 面临着部分转发节点路由容量较大的问题.而且物联子网中扁平化的地址结构使得这一问题更为突出.设计了支持IPv6 地址自动分配的轻量级树型转发模型TFAD（tree forwarding model with address automatically distributed），将物联子网中的节点构造成一棵层次转发树，树节点的IPv6 地址在子树范围内高度聚合.各节点只需存储与其子节点数相当的转发项，即可完成TFAD 模型的数据转发.此外，设计了TFAD 模型的备份父节点机制，当网络出现故障时能够以子树为单位进行网络拓扑重构，实现物联子网的快速路由恢复.实验验证了TFAD 模型的高效路由存储性能以及快速的路由学习能力和故障后路由恢复能力.

Light Weight and Tree-Based Forwarding Model in IPv6 IoT Subnet

RPL has received universal acceptance in IPv6 routing of the Internet of things (IoT). However, for large-scale multi-hops networks, the RPL routing model is faced with the problem that some IoT nodes heavily consume routing table storage. Besides, the flattened address architecture in IoT subnet makes this problem more prominent. In this paper, TFAD (tree forwarding model with address automatically distributed), a light-weight and tree-based forwarding model, is proposed to support automatic IPv6 address assignment. TFAD constructs a forwarding-level-tree for all the IoT nodes that make the IPv6 addresses of nodes aggregate highly in each sub-tree. In TFAD, each node only needs to maintain a few forwarding entries, the number of which is equivalent to the number of its direct son-nodes. Moreover, the backup mechanism of parent node in TFAD is designed. This mechanism supports the network topology reconstitution based on the whole sub-tree, achieving fast route-recovery from network failure. The experiments based on real sensor nodes prove that TFAD model possesses not only high performance on routing table storage but also rapidity on routing table learning and routing recovery from failure.