摘要
为了提高无线传感器网络覆盖性能,采用人工蜂群算法进行传感节点布置策略寻优,并对蜜源坐标分量进行混沌交叉,以增强人工蜂群算法的寻优能力。首先,根据目标区域选择合适的传感节点数,并建立针对目标区域的初始覆盖模型。接着,采用人工蜂群算法对覆盖模型进行优化求解,选择覆盖率作为适应度函数,将随机分布的所有传感节点坐标作为初始蜜源的位置。然后,进行探测蜂的候选蜜源搜索,获得适应度较高的传感节点坐标,并将候选蜜源坐标分量混沌优化。通过跟随蜂的分量优化,获得适应度最高的蜜源。最后,输出最优蜜源坐标,即为目标区域内所有传感节点的坐标值。试验结果表明,合理设置蜂群规模和迭代次数,相比于其他对比算法,混沌交叉人工蜂群算法能够获得更高的覆盖率。
In order to improve the coverage performance of wireless sensor networks,the artificial bee colony algorithm is used to optimize the sensor node layout strategy,and chaotic crossover of nectar source coordinate components is carried out to enhance the optimization ability of the artificial bee colony algorithm.Firstly,an appropriate number of sensor nodes is selected according to the target region,and an initial coverage model is established for the target region.Then,the artificial bee colony algorithm is used to optimize the coverage model,and the coverage rate is selected as the fitness function,and the coordinates of all sensor nodes randomly distributed are taken as the initial nectar source positions.Then,the candidate nectar source is searched by the probe bees to obtain the coordinates of the sensor nodes with higher fitness,and the candidate nectar source coordinate components are chaotically optimized.The nectar source with the highest fitness is obtained by components optimization of the following bees.Finally,the optimal nectar source coordinates are output,which are coordinate values of all sensor nodes in the target region.The experimental results show that,compared with the other three algorithms,the chaotic crossover artificial bee colony algorithm can achieve a higher coverage rate if the colony size and iteration times are set properly.
作者
谢珊
马琳娟
苏鑫
范智慧
Xie Shan;Ma Linjuan;Su Xin;Fan Zhihui(School of Information Engineering,Chengdu Vocational and Technical College of Industry,Chengdu 610213,China;School of Computer Science and Technology,Beijing Institute of Technology,Beijing 100081,China;School of Information and Software Engineering,University of Electronic Science and Technology of China,Chengdu 610054,China;College of Computer Science,Sichuan University,Chengdu 610065,China)
出处
《南京理工大学学报》
CAS
CSCD
北大核心
2024年第3期360-366,共7页
Journal of Nanjing University of Science and Technology
基金
国家自然科学基金(61871204)。
关键词
无线传感器网络
人工蜂群
混沌交叉
覆盖率
覆盖优化
wireless sensor network
artificial bee colony
chaotic crossover
coverage rate
coverage optimization
