發(fā)布時間：2019-03-18 19:38

【摘要】：為了提高網(wǎng)絡(luò)資源利用率延長網(wǎng)絡(luò)生存時間,提出一種基于共軛梯度法改進人工螢火蟲算法(CAGSO)的WSN覆蓋優(yōu)化方案;共扼梯度法是利用目標函數(shù)的梯度逐步產(chǎn)生共軛方向并將其作為搜索方向的方法,即利用已知點處的梯度構(gòu)造一組共扼方向并沿這組共扼方向進行搜索,這種方法經(jīng)有限次迭代必達極小點;首先建立以覆蓋率、節(jié)點利用率和能量均勻為準則的覆蓋優(yōu)化數(shù)學(xué)模型,然后采用改進的CAGSO算法求解該模型,從而得出最優(yōu)覆蓋方案;仿真分析說明,相比基本人工螢火蟲算法,改進的CAGSO算法優(yōu)化的網(wǎng)絡(luò)覆蓋率可以達到94.11%,有效實現(xiàn)WSN覆蓋優(yōu)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.
【作者單位】： 廣東石油化工學(xué)院實驗教學(xué)部計算機中心;廣東石油化工學(xué)院計算機與電子信息學(xué)院;
【分類號】：TP212.9;TN929.5;TP18

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