With the improvement of the MEMS (micro-electro-mechanical-systems), processor, radio and memory technologies, it’s possible to produce micro sensor nodes. These nodes capable of wireless communication, sensing and computation are extremely small, low-power and cheap price. Wireless sensor networks represent a significant improvement over traditional sensors.
A network of sensors can be used to obtain state-bases data from the area in which they are deployed. To reduce the costs, the data, sent via intermediate sensors to a sink, is often aggregated. And this aggregation is done by a subset of the sensors called aggregators.
In this paper, we set the aggregation model constructed by clusters which is divided into grids. Then we apply two different correlation algorithms that are spatial correlation and temporal correlation on different levels of aggregation in order to optimize the aggregation process. The experiments show that our algorithms improve our aggregation as expected.