Optimize the Data Collection Path in WSNs Based on the Neighbor Count of Path Points

Accomplishing data collection in WSNs by mobile elements (MEs) can reduce the amount of multi-hop communications in the network, which will decrease the energy consumption of sensors and prolong network lifetime. However, this may result in unacceptable data collection latency. The problem can be alleviated by reducing the traveling distance of the MEs with a genetic algorithm (GA) implementation. In this paper, we proposed an optimized GA initialization operator based on the neighbor count of path points, which can significantly improve the fitness of the initial population. We also modify the crossover operator to speed up the GA evolution process. Our method is testified by comprehensive experiments, and the results show that the length of data collection path got by the improved GA implementation is about 60% of the solutions got by the original one.