Data Aggregation Mechanisms on the Internet of Things: A Systematic Literature Review

Nowadays, the Internet of Things (IoT) has gained considerable attention in different academic and real-world research domains. Due to the data-driven nature of IoT, the data aggregation process in such systems is significantly challenging. The main goal of data aggregation mechanisms is to achieve high Quality of Services (QoS), including optimal data transmission delay, reliability, and energy consumption. Despite various types of available review papers on this particular topic, we feel that the existing literature does not satisfy the requirements of being up to date and comprehensive. This paper presents a systematic literature review for data aggregation mechanisms on IoT that illustrates the critical challenges in the context design issues. Further, the data aggregation mechanisms are divided into two main categories: client-server-based and mobile agent-based ones. The client-server-based data aggregation mechanisms are also presented in three groups: cluster-based, tree-based, and centralized methods. Finally, we outline possible future research trends in data aggregation on IoT.