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面向智慧教室的无线传感网边缘节点智能部署方法
引用本文:蒋金陵,徐胜超.面向智慧教室的无线传感网边缘节点智能部署方法[J].计算机测量与控制,2024,32(4):334-340.
作者姓名:蒋金陵  徐胜超
作者单位:广州华商学院  数据科学学院,广州华商学院  数据科学学院
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
摘    要:摘 要: 为降低部署后的通信时延,提高智慧教室的数据发送与网络使用效率,提出面向智慧教室的无线传感网边缘节点智能部署方法。以智慧教室场景中良好的通信、最大限度降低部署边缘节点成本为优化目标,构建边缘节点智能部署的目标函数。针对目标函数设定流量约束条件、无线传感网数据流约束条件、节点计算能力约束条件。自适应调整粒子群优化算法的惯性权重、粒子更新速度、Pareto最优解保存策略,设计多目标改进粒子群优化算法求解目标函数,实现面向智慧教室的无线传感网边缘节点智能部署。测试结果表明,该方法的时延较低,网络计算能力较高,保证了智慧教室无线传感网通信和传输质量。

关 键 词:关键词:  无线传感网  智慧教室  边缘节点  多目标改进粒子群优化算法  节点部署
收稿时间:2023/9/5 0:00:00
修稿时间:2023/10/14 0:00:00

Intelligent Deployment Method of Wireless Sensor Network Edge Nodes for Smart Classroom
Abstract:The communication quality and transmission effect of wireless sensor networks in smart classrooms are different under different edge node deployment modes. In order to reduce the communication delay after deployment and improve the efficiency of data transmission and network use in smart classrooms, an intelligent deployment method of wireless sensor network edge nodes for smart classrooms is proposed. The objective function of intelligent deployment of edge nodes is built with the optimization goal of good communication in the smart classroom scenario and minimizing the cost of deploying edge nodes. Set traffic constraints, data flow constraints and node computing capacity constraints for the objective function. Self adaptively adjust the inertia weight, particle update speed and Pareto optimal solution preservation strategy of the particle swarm optimization algorithm, design a multi-objective improved particle swarm optimization algorithm to solve the objective function, and achieve intelligent deployment of wireless sensor network edge nodes for smart classrooms. The test results show that? the proposed method has low delay and high network computing capacity, ensuring the communication and transmission quality of wireless sensor network in smart classrooms.
Keywords:Wireless sensor network  Smart classroom  Edge node  Multi-objective improved particle swarm optimization algorithm  Node deployment
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