Energy-Efficient and Privacy-Preserving Data Aggregation Algorithm for Wireless Sensor Networks

Abstract

Privacy-preserving data aggregation is a kind of fundamental and essential algorithm for wireless sensor networks. However, the existing aggregation algorithms consume a large amount of energy to assure sensory data security. In this article, we propose an energy-efficient and privacy-preserving data aggregation algorithm (EPDA). We organize a sensor network into a tree and connect the leaf nodes of the tree to form many chains. EPDA requires only the data sensed by the tail nodes of the chains to be sliced to ensure privacy. Also, EPDA significantly decreases energy consumption and prolongs the lifetime of the network. We compare our scheme with the existing schemes through theoretical analysis and simulations. The analysis and simulation results show that EPDA outperforms the existing schemes.