路径相似度因子在DV-Hop改进中的应用

经典DV-Hop方法在非均匀分布网络中存在节点间距离估计误差较大以及节点定位精度低的问题。引入节点间多跳最短路径相似度因子的计算规则,用于在距离估计步骤中修正节点的每跳平均距离值,并在位置计算步骤中选择参与定位计算的信标节点;使用改进的模拟退火(SA)算法对节点初始位置进行优化。仿真表明,所述改进策略在随机生成的网络拓扑结构条件下,相对于经典DV-Hop算法平均可降低约20%的定位误差,相对于既有的先进改进方法平均可降低约4%的定位误差,表现出良好的定位性能。

Application of path similarity factor in improvement of DV-Hop

The classical distance vector hop(DV Hop) method has the problem of error in distance estimation among nodes and low accuracy of node localization in non uniform distributed networks. The calculation rule of similarity factor for multi hop shortest path among nodes is introduced, which is used to correct the hop size of a node in the distance estimation step, and to select the beacon node involved in localization calculation in the position calculation step. The initial position of a node is optimized using an improved simulated annealing (SA) algorithm. The simulation results show that under the condition of randomly generated network topology, the improved strategy can reduce the positioning error by about 20% on average compared with the classical DV Hop algorithm, and about 4% on average compared with the existing methods, which shows good positioning performance.