Reducing the data transmission in Wireless Sensor Networks using the Principal Component Analysis

Aggregation services play an important role in the domain of Wireless Sensor Networks (WSNs) because they significantly reduce the number of required data transmissions, and improve energy efficiency on those networks. In most of the existing aggregation methods that have been developed based on the mathematical models or functions, the user of the WSN has not access to the original observations. In this paper, we propose an algorithm which let the base station access the observations by introducing a distributed method for computing the Principal Component Analysis (PCA). The proposed algorithm is based on transmission workload of the intermediate nodes. By using PCA, we aggregate the incoming packets of an intermediate node into one packet and as a result, an intermediate node merely sends a packet instead of relaying all the incoming packets. Consequently, we can achieve considerable reduction in data transmission. We have analyzed the performance of the proposed algorithm through numerical simulations. The experimental results show that our algorithm performs better than the existing state of the art PCA-based aggregation algorithms such as PCAg in terms of accuracy and efficiency.