Dynamic adjustment strategy of sensor nodes based on artificial fish swarm algorithm

Coverage is the basic factor for the normal work of a sensor network, and the effect of network coverage directly affects the monitoring performance of a wireless sensor network. This paper proposes a dynamic adjustment strategy for sensor nodes based on the artificial fish swarm algorithm. The strategy first uses the fixed location deployment to place the sensor nodes, which can achieve full coverage of the monitoring region under the condition of relatively few nodes. After the deployment, the strategy uses the preliminary adjustment based on the artificial fish swarm algorithm to expand the sensing directions of sensor nodes to get the maximum coverage. Next, once the target appears, the sensor nodes optimally regulate their sensing directions again to obtain the best monitoring visual effect. Finally, the strategy designs a method for selecting the best node. According to it, the best node is automatically selected as the working node to perform monitoring, data processing, and transmission. By this means, the amount of monitoring data can be reduced, and the energy consumption of nodes can be balanced. Experimental results show that the proposed strategy can not only obtain greater coverage and better monitoring effect, but also extend the network's life.