面向应急监测通信网时空覆盖优化的递阶遗传算法  

A Hierarchical Genetic Algorithm for Spatio-Temporal Coverage Optimization in Communication Networks under Emergency Monitoring Scenarios

作　　者：胡文焯 吴春 HU Wenzhuo;WU Chun(Wuhan Natural Resources Conservation and Utilization Center,Wuhan 430014,China)

机构地区：[1]武汉市自然资源保护利用中心,武汉430014

出　　处：《地球信息科学学报》2024年第8期1880-1892,共13页Journal of Geo-information Science

摘　　要：大规模突发环境事故往往会损害受灾地区光缆、基站等网络基础设施,亟需借助现有通讯设备搭建临时的自组织通信网络以传输污染物浓度等应急监测数据,使应急指挥中心及时判别污染态势并制定相应挽救策略。因此地空通信网覆盖部署成为断网场景下应急监测任务顺利实施的关键。本文采用空间分析方法驱动应急通信车至最佳位置,基于此设计具有时空递阶染色体矩阵、适应度综合评价模型、协同进化机制的混合递阶遗传算法,智能化部署通信节点以组建时空覆盖的地空通信网,实现监测数据自主传输。算法综合考虑应急监测人员分布、气候条件、通信资源工作状况及通信性能等因素,若偶发通信资源新增或失效、通信需求调整等变动,支持适应性更新现场通信节点时空位置和通信链路。以新疆一处尾矿库为实验样区进行验证分析,基于三维地球平台可视化地空通信网部署方案并评估算法适应度收敛能力、动态场景应变性和实地实施效力。本算例适应度经260次迭代后约提升30%,相较于随机搜索等其他5种算法展现出更优越的收敛速度和提升幅度,通信节点在续航时间内保障了不同场景监测任务点的全面覆盖和均衡分配,满足实地应急监测响应需求,证明了算法可靠性、可行性。Large-scale sudden environmental incidents often disrupt network infrastructures such as fiber cables and base stations.Establishing a special self-organizing network for emergency monitoring data transmission is essential for effective disaster response.Utilizing spatial analysis techniques,this paper guides the emergency communication vehicle to a strategically advantageous position.Building on this,considering factors such as the distribution of emergency personnel,communication performance,and climate conditions,this research intelligently deploys communication drones and establishes communication links to form an emergency terrestrial-aerial communication network using a hybrid hierarchical genetic algorithm.This includes designing a spatio-temporal hierarchical chromosome matrix,a comprehensive fitness evaluation model,and a co-evolutionary mechanism to achieve adaptive transmission of monitoring data.In the event of unexpected changes such as the addition or failure of communication resources or adjustments to communication requirements,the algorithm adaptively updates the deployment positions of emergency communication resources and communication links.This method was validated and analyzed using a tailings pond in Xinjiang as an experimental area.The deployment solutions were visualized on a 3D Earth platform,and the fitness convergence ability,dynamic adjustability,and implementation effectiveness were evaluated.The algorithm demonstrated an approximate 30% improvement in fitness after 260 iterations,showing a higher convergence speed and improvement amplitude compared to other five algorithms such as random search.The communication nodes achieved comprehensive coverage and balanced distribution of monitoring points under different scenarios within the endurance period,meeting the requirements for on-site emergency monitoring response,thereby proving the algorithm's reliability and feasibility.

关 键 词：应急通信车 通信无人机 通信时空覆盖 通信链路 应急监测 递阶遗传算法 粒子群算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TN91[自动化与计算机技术—控制科学与工程]