Data aggregation algorithm for wireless sensor network based on time prediction
Mingxin Yang · 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference (ITOEC) · 2017
In wireless sensor networks, sensor nodes are often deployed intensively within the sensing area in order to achieve effective monitoring, resulting in a high degree of correlation between them. There is a certain variation rule between node acquisition data and time. The current time correlation will result in an abundance of redundant data within the sensing area, so eliminating data redundancy is the fundamental way to save network energy consumption. In this paper, a data fusion algorithm FTDA based on the time prediction model is proposed in view of the problems of scalability of the prediction model and the ability to proactively identify data redundancy. The simulation results show that the algorithm can extend the network lifetime and save energy consumption.