A Novel Data Aggregation Scheme for Wireless Sensor Networks Based on Robust Chinese Remainder Theorem

Abstract

In wireless sensor networks (WSNs), to improve sensing accuracy and coverage, a large number of sensor nodes are usually deployed in the monitoring area. The high density makes the data sensed by adjacent sensor nodes the same or similar, causing a lot of data redundancy and energy waste. In addition, reliability and non-plaintext transmission of the sensed data are also major concerns in WSNs. In this paper, we propose a novel data aggregation scheme to satisfy the requirements of energy efficiency, reliability, and non-plaintext transmission simultaneously, which obtains the approximate measurement result when small measurement errors are allowed. The scheme employs robust Chinese Remainder Theorem (RCRT) to compress the data when it is sensed and no other assumptions are required. We further derive some analytical results and give the simulation results of our scheme. Finally, we compare the performance of the typical data aggregation schemes with our RCRT-based data aggregation scheme in experimental simulation. The results demonstrate that the proposed RCRT-based data aggregation scheme has a better performance in energy saving.