Genetic algorithm for data aggregation trees in wireless sensor networks

This paper uses a genetic algorithm (GA) to generate balanced and energy efficient data aggregation spanning trees for wireless sensor networks. In a data gathering round, a single best tree consumes lowest energy from all nodes but assigns more load to some sensors. As a result, the energy resources of heavily loaded nodes will be depleted earlier than others. Therefore, we use a collection of trees that balances load among nodes and consumes less energy. Our proposed GA takes these two issues in generating aggregation trees. The GA is simulated in an open source simulator, J-sim. The simulation results show that proposed GA outperforms a few other data aggregation tree-based approaches in terms of extending network lifetime.