4.6 Article

Wireless Sensor Network Deployment Optimization Based on Two Flower Pollination Algorithms

期刊

IEEE ACCESS
卷 7, 期 -, 页码 180590-180608

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2959949

关键词

Deployment optimization; improved flower pollination algorithm; non-dominated sorting; multi-objective flower pollination algorithm; wireless sensor networks

资金

  1. National Natural Science Foundation of China [61562037, 61562038, 61563019, 61763017, U1936120, U1636216]
  2. National Key Research and Development Program of China [2017YFB0802805, 2017YFB0801701]
  3. Natural Science Foundation of Jiangxi Province [20171BAB202026, 20181BBE58018]
  4. Science and Technology Project [GJJ150643]
  5. Innovation Designated Fund for Graduate Student of Jiangxi Province [YC2018-S331]

向作者/读者索取更多资源

For the wireless sensor networks (WSNs) heterogeneous node deployment optimization problem with obstacles in the monitoring area, two new flower pollination algorithms (FPA) are proposed to deploy the network. Firstly, an improved flower pollination algorithm (IFPA) is proposed based on FPA, aiming at the shortcomings of the convergence speed is slow and the precision is not high enough of FPA. The nonlinear convergence factor is designed to correct the scaling factor of FPA, the Tent chaotic map effectively maintains the diversity of the population in the late iteration, and a greedy crossover strategy is designed to assist the remaining individual search with better individuals. Secondly, based on FPA, a non-dominated sorting multi-objective flower pollination algorithm (NSMOFPA) is proposed. The external archive strategy and leader strategy are introduced, to solve the global pollination problem. The proposed crowding degree method and the introduced elite strategy effectively maintain the diversity of the population. Then, IFPA is applied to WSN deployment aiming at optimizing coverage rate, simulation experiments show that IFPA can obtain a higher coverage rate with shorter iterations, which can save network deployment costs. Finally, applying NSMOFPA to the WSN deployment with optimization objectives for coverage rate, node radiation overflow rate and energy consumption rate. The experimental results verify that NSMOFPA has a good optimization effect and can provide a better solution for WSN deployment.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据