Efficient data management in Internet of Things: A survey of data aggregation techniques

Article type: Research Article

Authors: Kang, Xiaoqiang^{a; *}

Affiliations: Zhengzhou College of Electronics and Information Technology, Zhengzhou, China

Correspondence: [*] Corresponding author. Xiaoqiang Kang, Zhengzhou College of Electronics and Information Technology, Zhengzhou 451450, China. E-mail: kangxq2020@126.com.

Abstract: The Internet of Things (IoT) refers to a vast network of interconnected devices, objects, and systems powered by sensors, software, and connectivity capabilities. The interconnectivity of IoT devices has led to a substantial increase in data production. Efficiently managing and analyzing large data volumes is a significant challenge for IoT systems. To address this challenge, data aggregation is the primary process. IoT data aggregation aims to provide high-quality service by ensuring fast data transmission, high reliability, minimal energy consumption, and data priority consideration. Data aggregation involves collecting data from multiple sensors and devices and then integrating it using a function to minimize system traffic. This paper thoroughly examines data aggregation techniques in the IoT context. Techniques are grouped according to underlying principles, and their potential applications, advantages, and limitations are discussed.

Keywords: Internet of things, data aggregation, data transmission, energy consumption

DOI: 10.3233/JIFS-238284

Journal: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 4, pp. 9607-9623, 2024