基于改进人工萤火虫算法的无线传感网络覆盖优化
发布时间：2019-03-18 19:38
【摘要】：为了提高网络资源利用率延长网络生存时间,提出一种基于共轭梯度法改进人工萤火虫算法(CAGSO)的WSN覆盖优化方案;共扼梯度法是利用目标函数的梯度逐步产生共轭方向并将其作为搜索方向的方法,即利用已知点处的梯度构造一组共扼方向并沿这组共扼方向进行搜索,这种方法经有限次迭代必达极小点;首先建立以覆盖率、节点利用率和能量均匀为准则的覆盖优化数学模型,然后采用改进的CAGSO算法求解该模型,从而得出最优覆盖方案;仿真分析说明,相比基本人工萤火虫算法,改进的CAGSO算法优化的网络覆盖率可以达到94.11%,有效实现WSN覆盖优化。
[Abstract]:In order to improve the utilization rate of network resources and prolong the network lifetime, a WSN coverage optimization scheme based on conjugate gradient method is proposed to improve the artificial firefly algorithm (CAGSO). The conjugate direction is gradually generated by the gradient of the objective function and used as the search direction. That is to say, the gradient at the known point is used to construct a group of conjugate directions and search along the conjugate directions. This method must reach the minimum point after finite iterations. Firstly, a mathematical model of coverage optimization based on coverage ratio, node utilization ratio and energy uniformity is established, and then the improved CAGSO algorithm is used to solve the model, thus the optimal coverage scheme is obtained. Simulation analysis shows that compared with the basic artificial firefly algorithm, the network coverage of the improved CAGSO algorithm can reach 94.11%, and the WSN coverage optimization can be realized effectively.
【作者单位】： 广东石油化工学院实验教学部计算机中心;广东石油化工学院计算机与电子信息学院;
【分类号】：TP212.9;TN929.5;TP18
[Abstract]:In order to improve the utilization rate of network resources and prolong the network lifetime, a WSN coverage optimization scheme based on conjugate gradient method is proposed to improve the artificial firefly algorithm (CAGSO). The conjugate direction is gradually generated by the gradient of the objective function and used as the search direction. That is to say, the gradient at the known point is used to construct a group of conjugate directions and search along the conjugate directions. This method must reach the minimum point after finite iterations. Firstly, a mathematical model of coverage optimization based on coverage ratio, node utilization ratio and energy uniformity is established, and then the improved CAGSO algorithm is used to solve the model, thus the optimal coverage scheme is obtained. Simulation analysis shows that compared with the basic artificial firefly algorithm, the network coverage of the improved CAGSO algorithm can reach 94.11%, and the WSN coverage optimization can be realized effectively.
【作者单位】： 广东石油化工学院实验教学部计算机中心;广东石油化工学院计算机与电子信息学院;
【分类号】：TP212.9;TN929.5;TP18
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