A Novel WSNs Localization Algorithm Based on Artificial Fish Swarm Algorithm


  • Xiaoying Yang
  • Wanli Zhang
  • Qixiang Song




wireless sensor networks, artificial fish swarm algorithm, least square method, node localization


In node localization algorithm in Wireless Sensor Networks (WSNs), the least square method is affected by the measurement error, which leads to position error of the unknown node. In order to solve the problem that the error is too high, we propose a novel WSNs localization algorithm based on artificial fish swarm (AFSA). In the proposed algorithm, artificial fish swarm, which has some advantages such as requirements for the initial value and parameter setting is not high, the optimization speed is quick and so on, is introduced in position process. Firstly, the distances between nodes are obtained by using the TDOA algorithm. Then the geometrical position of the unknown nodes is estimated by the artificial fish swarm optimization algorithm. The simulation results show that compared with the least square method, the algorithm proposed in the paper can reduce the computation amount, get the optimal solution quickly and improve the accuracy of the node without increasing the cost and power consumption. Moreover, the number of beacon nodes is relatively small, so the network cost is reduced to a certain extent.




How to Cite

Yang, X., Zhang, W., & Song, Q. (2016). A Novel WSNs Localization Algorithm Based on Artificial Fish Swarm Algorithm. International Journal of Online and Biomedical Engineering (iJOE), 12(01), pp. 64–68. https://doi.org/10.3991/ijoe.v12i1.5180