A Coverage Optimization Algorithm for the Wireless Sensor Network with Random Deployment by Using an Improved Flower Pollination Algorithm

Abstract

Due to complex terrain and harsh environments, sensor nodes are often randomly scattered in the monitoring area, which may cause coverage holes or network disconnection. Current works move some sensor nodes to certain places to address this problem. However, these works cannot guarantee the coverage and connectivity simultaneously and have larger moving cost in energy. In this paper, we propose a coverage optimization strategy based on the flower pollination algorithm (FPA). First, to solve the shortcomings of the classical FPA in convergence and accuracy, an improved FPA is proposed. Then, the network deployment optimization problem is modeled as a multi-objective optimization problem that guarantees the coverage of target points and the connectivity of the network while minimizing the energy consumption of sensor nodes’ moving. The sensor nodes are selected and moved to the proper position by utilizing the improved FPA to minimize the energy consumed by the sensors’ motion and guarantee the coverage and connectivity. Test results show that the improved FPA has good convergence speed and accuracy compared with other evolutionary algorithms. Simulation results demonstrate that the proposed algorithm can guarantee network connectivity and satisfy the coverage requirement while minimizing the energy consumption of the sensor movement. Consequently, more energy of the sensor node can be used to collect and transmit sensed data. These results indicate that our algorithm can prolong network lifetime and improve monitoring quality in fields such as forest monitoring.

Sensor Topology Optimization in Dense IoT Environments by Applying Neural Network Configuration

“…Following on from this, nature-inspired optimization algorithms are adopted by many researchers in WSN applications [14]. While genetics, ants, and particle swarm algorithms are the dominant examples, many others emerge regularly such as the flower pollination algorithm (FPA), which is a novel global optimization algorithm inspired by the pollination process of flowers [14]. Based on the multiobjective version of the FPA (i.e., MOFPA) for WSNs, a new approach is proposed in [15].…”

Optimal Deployment for Hybrid Sensor Networks Based on Efficient Node Configuration

“…In diferent deployment environments, VF-IMFO algorithm maintains signifcant performance advantages. Jiao et al proposed a coverage optimization strategy based on fower pollination algorithm (FPA) [24]. First, an improved FPA is proposed in view of the shortcomings of classical FPA in convergence and accuracy.…”