一种有向视频传感器网络改进MPSO覆盖增强算法
An Improved MPSO Coverage Enhancement Algorithm for Directional Video Sensor Networks
摘要: 针对有向视频摄像机传感器网络的目标检测区域的覆盖服务问题,基于部署位置固定仅可连续旋转的传感器节点,增加可连续移动的轨道,提出可移动节点的传感器网络模型。基于MPSO算法,将变异思想结合系数改进的PSO算法进行改进,通过选取合适的粒子搜索策略得到改进的MPSO算法,并将其应用于求解可移动节点的传感器网络模型。在仿真实验中,通过与PSO算法、系数改进的PSO算法的比较,验证了改进的MPSO算法的有效性。一方面验证了新模型对于问题最优解更大的搜索空间,另一方面也实现了最大化覆盖区域和最小化重叠区域的目标。
Abstract: For the coverage service problem of the target detection area of the directional video camera sensor network, the sensor network model of the movable nodes is proposed by adding continuously movable tracks, which is based on the sensor nodes with fixed positions and can be continuously rotated. In this paper, an improved MPSO algorithm combining with adaptive idea and variational idea is proposed and applied to solve the sensor network model of movable nodes by selecting suitable particle search strategies, which is based on MPSO algorithm. In the simulation experiments, the effectiveness of the improved MPSO algorithm is verified by comparing with the PSO algorithm and the improved PSO algorithm. For one thing, it is verified that the new model has a larger search space for the optimal solution of the problem, for another it achieves the goal of maximizing the covered area and minimizing the overlapped area.
文章引用:秦芳芳, 张珈瑞, 蔡云峰. 一种有向视频传感器网络改进MPSO覆盖增强算法[J]. 理论数学, 2024, 14(7): 284-296. https://doi.org/10.12677/pm.2024.147294

参考文献

[1] 黄俊杰, 孙力娟, 王汝传, 等. 三维水下传感器网络覆盖优化算法[J]. 南京邮电大学学报(自然科学版), 2013, 33(5): 69-74.
[2] 韩崇, 孙力娟, 郭剑. 一种基于网格划分的有向传感网时空覆盖调度算法[J]. 南京邮电大学学报(自然科学版), 2013, 33(5): 82-87.
[3] Zhang, K., Jia, H. and Lv, H. (2016) Coverage-Enhancing Approach in Multimedia Directional Sensor Networks for Smart Transportation. Multimedia Tools and Applications, 75, 17593-17615. [Google Scholar] [CrossRef
[4] Zhang, F., Ding, G., Xu, L., Chen, B. and Li, Z. (2018) An Effective Method for the Abnormal Monitoring of Stage Performance Based on Visual Sensor Network. International Journal of Distributed Sensor Networks, 14. [Google Scholar] [CrossRef
[5] Zhang, X., Chen, X., Farzadpour, F. and Fang, Y. (2018) A Visual Distance Approach for Multicamera Deployment with Coverage Optimization. IEEE/ASME Transactions on Mechatronics, 23, 1007-1018. [Google Scholar] [CrossRef
[6] Ma, H. and Liu, Y. (2005) On Coverage Problems of Directional Sensor Networks. Mobile Ad-hoc and Sensor Networks, Wuhan, 13-15 December 2005, 721-731. [Google Scholar] [CrossRef
[7] 陶丹, 马华东, 刘亮. 基于虚拟势场的有向传感器网络覆盖增强算法[J]. 软件学报, 2007, 18(5): 1152-1163.
[8] 徐义春, 雷帮军. 摄像机网络整体视域优化扩展模型及最优求解[J]. 计算机应用研究, 2010, 27(5): 1676-1679.
[9] Xu, Y., Lei, B. and Hendriks, E.A. (2011) Camera Network Coverage Improving by Particle Swarm Optimization. EURASIP Journal on Image and Video Processing, 2011, Article No. 458283.
[10] Zhou, P. and Long, C. (2011) Optimal Coverage of Camera Networks Using PSO Algorithm. 2011 4th International Congress on Image and Signal Processing, Shanghai, 15-17 October 2011, 2084-2088. [Google Scholar] [CrossRef
[11] Xu, Y., Lei, B. and Hendriks, E.A. (2013) Constrained Particle Swarm Algorithms for Optimizing Coverage of Large-Scale Camera Networks with Mobile Nodes. Soft Computing, 17, 1047-1057. [Google Scholar] [CrossRef
[12] Fu, X. and Zeng, J. (2015) Coverage-Enhancing Algorithm for Video Sensor Network Based on Improved Particle Swarm Optimization. Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering, Zhengzhou, 11-13 April 2015, 446-450. [Google Scholar] [CrossRef
[13] 符祥, 袁泽敏. 基于改进PSO的视频传感器网络覆盖增强算法[J]. 图像与信号处理, 2020, 9(4): 188-193.
[14] Tian, D. and Shi, Z. (2018) MPSO: Modified Particle Swarm Optimization and Its Applications. Swarm and Evolutionary Computation, 41, 49-68. [Google Scholar] [CrossRef
[15] Ni, Q., Du, H., Pan, Q., Cao, C. and Zhai, Y. (2015) An Improved Dynamic Deployment Method for Wireless Sensor Network Based on Multi-Swarm Particle Swarm Optimization. Natural Computing, 16, 5-13. [Google Scholar] [CrossRef
[16] Kennedy, J. and Eberhart, R. (1995) Particle Swarm Optimization. Proceedings of ICNN’95-International Conference on Neural Networks, Perth, 27 November-1 December 1995, 1942-1948. [Google Scholar] [CrossRef
[17] Jiang, Y., Hu, T., Huang, C. and Wu, X. (2007) An Improved Particle Swarm Optimization Algorithm. Applied Mathematics and Computation, 193, 231-239. [Google Scholar] [CrossRef
[18] 宋梦培, 莫礼平, 周恺卿. 惯性权值和学习因子对标准PSO算法性能的影响[J]. 吉首大学学报(自然科学版), 2019, 40(4): 24-32.