摘要
无线传感器网络在远程监控和目标跟踪等场景中具有重要意义,当前亟待解决的问题是如何提高数据传输质量并提升网络生命周期。本文提出了一种基于剩余能量的优化分簇算法,对簇头节点进行合理的选取。这种算法有效改善了网络中部分节点过早衰亡进而影响整网寿命周期的现象。同时,提出了神经网络融合算法的权重修正模型,修正后的算法可以降低向汇聚节点传输的数据包数量,延长整网生命周期。通过软件仿真测试结果证明,以上两种节能算法均可有效优化无线传感器网络能耗,提升网络寿命。
Wireless sensor network plays an important role in remote monitoring and target tracking.The problem that needs to be solved urgently is how to improve the data transmission quality and enhance the network life cycle.In this paper,an optimized clustering algorithm based on residual energy is proposed to select the cluster head nodes reasonably.This algorithm can effectively improve the phenomenon that some nodes in the network die prematurely,and then affect the life cycle of the whole network.At the same time,a weight correction model of neural network fusion algorithm is proposed.The modified algorithm can reduce the number of packets transmitted to aggregation nodes and extend the whole network life cycle.The software simulation results show that the above two energy-saving algorithms can effectively optimize the energy consumption of wireless sensor networks and improve the network life.
作者
宋严
SONG Yan(Network Center of Changchun Normal University,Changchun 130032,China)
出处
《长春师范大学学报》
2023年第10期29-34,70,共7页
Journal of Changchun Normal University
基金
吉林省教育厅科学技术研究基金项目“基于智慧城市数据监测的5G无线传感器网络高速数据传输模式研究”(JJKH20210888KJ)。
关键词
无线传感器网络
生命周期
分簇算法
神经网络算法
wireless sensor network
node energy consumption
clustering algorithm
neural network algorithms
