论文部分内容阅读
传统光学传输网络邻居节点发现方法存在节点识别耗时长、准确率低等不足。提出一种基于物联网的光学传输网络邻居节点快速发现方法研究,首先利用物联网的联通性构建一种扇形节点感知模型,判定当前节点感知区域范围内存在邻居节点的可能性;采用最小二乘法原理对感知区域内存在的邻居节点进行模糊定位,对现有节点周围的未知邻居节点设定适当的约束条件,将节点定位问题转化为约束优化问题,最后利用粒子群算法实现光学传输网络邻居节点的寻优和定位。实验证明提出的方法能够快速地发现邻居节点、识别率高、误差率低。
The traditional method of node discovery in optical transport network has the disadvantages of long node identification, low accuracy and so on. This paper presents a new method for fast discovery of neighbor nodes in optical transport networks based on Internet of Things. First, a fan-shaped node awareness model is constructed based on IoT connectivity to determine the possibility of neighbor nodes existing in the perceptual region of the current node. Least- The principle is to locate the neighboring nodes in the sensing area, set the appropriate constraints for the unknown nodes in the vicinity of the existing nodes, and transform the node localization problem into the constrained optimization problem. Finally, the particle swarm optimization algorithm is used to realize the neighbor nodes The optimization and positioning. Experimental results show that the proposed method can quickly find neighbor nodes with high recognition rate and low error rate.