基于凝聚机制的移动物联网数据融合算法  

Data fusion algorithm for mobile internet of things based on aggregation mechanism

作　　者：王恒[1] Wang Heng(School of Electronics and Information Engineering,Jingchu University of Technology,Jingmen 448000,China)

机构地区：[1]荆楚理工学院电子信息工程学院,荆门448000

出　　处：《国外电子测量技术》2021年第7期19-23,共5页Foreign Electronic Measurement Technology

基　　金：荆门市科技局科研项目(2019YDKY078)资助。

摘　　要：为降低移动物联网部署过程中存在的数据融合性能不强、网络能耗难以控制的不足,提出了一种基于凝聚机制的移动物联网数据融合算法。首先,针对移动物联网路由抖动现象,设计了基于凝聚机制的数据融合爬取方法,将具有相似特性的数据进行融合传输,从而提高数据融合质量。其次,针对路径转折所导致的传输波动问题,设计了基于偏转方法的骨干传输路径修正机制,通过动态调整下一跳节点来增强网络对链路抖动的适应,强化动态链路对传输数据的控制强度。随后,算法依据路径筛选凝聚因子,选取具有较高凝聚因子的节点作为下一跳节点,从而提高网络对传输路径的筛选质量,仿真结果表明,所提算法在节点低速运动时可将数据融合率维持在80%,能耗不高于150 J/min,节点高速运动时的数据融合率依然维持在50%~70%,能耗不高于280 J/min,均要显著优于对照组算法,呈现出更低的网络能耗和更高的融合率。In order to reduce the shortcomings of weak data fusion performance and difficult control of network energy consumption in the deployment process of mobile Internet of things, a data fusion algorithm based on aggregation mechanism for mobile Internet of things is proposed. Firstly, aiming at the routing jitter phenomenon of mobile Internet of things, a data fusion crawling method based on aggregation mechanism is designed to fuse and transmit data with similar characteristics, so as to improve the quality of data fusion. Secondly, aiming at the problem of transmission fluctuation caused by path transition, a backbone transmission path correction mechanism based on deflection method is designed. By dynamically adjusting the next hop node, the network can adapt to link jitter and strengthen the control strength of dynamic link to transmission data. Then, the algorithm selects the node with higher cohesion factor as the next hop node according to the path selection, so as to improve the quality of network transmission path selection. The simulation results show that the proposed algorithm can maintain the data fusion rate at 80% when the node is moving at low speed, the energy consumption is not higher than 150 J/min, and the data fusion rate is still maintained at 50% ~ 70% when the node is moving at high speed, Energy consumption is not higher than 280 J/min, which is significantly better than the control group algorithm, showing lower network energy consumption and higher convergence rate.

关 键 词：移动物联网 凝聚 融合爬取 多径传输 路径更新 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]