Energy-Balanced Density Control to Avoid Energy Hole for Wireless Sensor Networks

Density control is of great relevance for wireless sensor networks monitoring hazardous applications where sensors are deployed with high density. Due to the multihop relay communication and many-to-one traffic characters in wireless sensor networks, the nodes closer to the sink tend to die faster, causing a bottleneck for improving the network lifetime. In this paper, the theoretical aspects of the network load and the node density are investigated systematically. And then, the accessibility condition to satisfy that all the working sensors exhaust their energy with the same ratio is proved. By introducing the concept of the equivalent sensing radius, a novel algorithm for density control to achieve balanced energy consumption per node is thus proposed. Different from other methods in the literature, a new pixel-based transmission mechanism is adopted, to reduce the duplication of the same messages. Combined with the accessibility condition, nodes on different energy layers are activated with a nonuniform distribution, so as to balance the energy depletion and enhance the survival of the network effectively. Extensive simulation results are presented to demonstrate the effectiveness of our algorithm

A Rapid Localization Method Based on Super Resolution Magnetic Array Information for Unknown Number Magnetic Sources

A rapid method that uses super-resolution magnetic array data is proposed to localize an unknown number of magnets in a magnetic array. A magnetic data super-resolution (SR) neural network was developed to improve the resolution of a magnetic sensor array. The approximate 3D positions of multiple targets were then obtained based on the normalized source strength (NSS) and magnetic gradient tensor (MGT) inversion. Finally, refined inversion of the position and magnetic moment was performed using a trust region reflective algorithm (TRR). The effectiveness of the proposed method was examined using experimental field data collected from a magnetic sensor array. The experimental results showed that all the targets were successfully captured in multiple trials with three to five targets with an average positioning error of less than 3 mm and an average time of less than 300 ms