Approximate Data Aggregation in Sensor Equipped IoT Networks

• 来源期刊: 清华大学学报自然科学版（英文版）
• 年，卷（期）: 2020,（1）
• 页码范围: 44-55
• 页数: 12页
• 语种: 英文
• DOI: 10.26599/TST.2019.9010023

摘要

As Internet-of-Things (IoT) networks provide efficient ways to transfer data,they are used widely in data sensing applications.These applications can further include wireless sensor networks.One of the critical problems in sensor-equipped IoT networks is to design energy efficient data aggregation algorithms that address the issues of maximum value and distinct set query.In this paper,we propose an algorithm based on uniform sampling and Bernoulli sampling to address these issues.We have provided logical proofs to show that the proposed algorithms return accurate results with a given probability.Simulation results show that these algorithms have high performance compared with a simple distributed algorithm in terms of energy consumption.