Data Aggregation in Wireless Sensor Networks: Emerging Research Areas
Damilola Nnamaka Ajobiewe · Journal of Mathematical Sciences & Computational Mathematics · 2021
Wireless Sensor Networks (WSNs) generate an immense measure of explicit data usage. Such data, which is an exorbitant issue, should be prepared and then transmitted to the base station. Efficient data handling and energy monitoring are primary challenges since WSN hubs are asset-compelled. The point of wireless sensor networks is not confined to data collection in the present climate. Yet the retrieval of beneficial data still depends on it. The term used for the retrieval of beneficial data is data aggregation. In social affairs, data aggregation helps to collect data in energy-efficient ways to elongate the network's duration. The majority of the detected data by the sensors were seen to be excessive. On the off chance that data repetition can be reduced, it will prompt the organization's extended lifetime and decreased inertness at that point. This paper explains a wide methodological analysis of literature on data aggregation in WSNs. Review of various strategies to reduce data repetition, and specifically through aggregation, as well as scientific categorization of data aggregation, challenges, and broken-down aggregation methods proposed over the last ten (10) years, are discussed.