一种混沌萤火虫算法的WSN节点分布优化研究
发布时间：2018-09-04 20:14
【摘要】：针对无线传感器网络节点分布优化问题,提出了一种有效的混沌萤火虫优化算法。在保证节点相互连通的前提下,建立了无线传感器网络对目标区域覆盖的数学模型,并将节点分布优化问题转换为求解函数最大值问题;利用萤火虫算法优越的寻优能力来实现最优的网络节点分布,并引入立方映射混沌算子来提高算法的局部搜索能力和保持种群的多样性。通过标准函数测试与无线网络覆盖优化仿真对所提算法进行了验证,结果表明:与其他算法相比,所提算法能够较好地跳出局部最优的束缚,具有优化效果佳、稳定性好、鲁棒性强的优点,能够满足无线传感器网络节点分布优化的要求。
[Abstract]:To solve the problem of node distribution optimization in wireless sensor networks, an effective chaotic firefly optimization algorithm is proposed. On the premise that nodes are connected to each other, the mathematical model of wireless sensor network covering the target area is established, and the optimization problem of node distribution is transformed into solving the maximum function problem. The optimal network node distribution is realized by using the superior optimization ability of the firefly algorithm, and the cubic mapping chaotic operator is introduced to improve the local search ability of the algorithm and to maintain the diversity of the population. The proposed algorithm is verified by standard function test and wireless network coverage optimization simulation. The results show that compared with other algorithms, the proposed algorithm can jump out of the bondage of local optimum, and has good optimization effect and stability. Because of its strong robustness, it can meet the requirements of node distribution optimization in wireless sensor networks.
【作者单位】： 江苏信息职业技术学院;南京航空航天大学;
【基金】：江苏省高校品牌专业建设工程资助项目(PPZY2015B190)
【分类号】：TP18;TP212.9;TN929.5
本文编号：2223214
[Abstract]:To solve the problem of node distribution optimization in wireless sensor networks, an effective chaotic firefly optimization algorithm is proposed. On the premise that nodes are connected to each other, the mathematical model of wireless sensor network covering the target area is established, and the optimization problem of node distribution is transformed into solving the maximum function problem. The optimal network node distribution is realized by using the superior optimization ability of the firefly algorithm, and the cubic mapping chaotic operator is introduced to improve the local search ability of the algorithm and to maintain the diversity of the population. The proposed algorithm is verified by standard function test and wireless network coverage optimization simulation. The results show that compared with other algorithms, the proposed algorithm can jump out of the bondage of local optimum, and has good optimization effect and stability. Because of its strong robustness, it can meet the requirements of node distribution optimization in wireless sensor networks.
【作者单位】： 江苏信息职业技术学院;南京航空航天大学;
【基金】：江苏省高校品牌专业建设工程资助项目(PPZY2015B190)
【分类号】：TP18;TP212.9;TN929.5
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