A Multifactorial Evolutionary Algorithm For Minimum Energy Cost Data Aggregation Tree In Wireless Sensor Networks

In wireless sensor networks, the majority of data transmitted by sensor nodes is repeated over and over, and performing processes on them in many cases leads to increased power consumption and reduced network lifetime. Data aggregation is one of the techniques in reducing redundancy and improving energy efficiency; it also increases the lifespan of wireless sensor networks. In this paper, we address the issues of constructing the data aggregation tree that minimizes the total energy cost of data transmissions for two types of networks: without relay nodes and using relay nodes. Traditionally, evolutionary algorithms focus on constructing data aggregation trees for either without relay node networks or using relay nodes networks. Therefore, we propose Potential individuals based Multi-factorial Evolutionary Algorithm (P-MFEA) to solve both issues simultaneously. The proposed scheme shows improved performance in terms of energy consumption.