Abstract:
In numerous Internet of Things contexts, there is an increasing interest to use wireless sensor technologies. One of the most
difficult problems is gathering and analyzing commodity data, given the enormous rise of smart objects and their applications. Sensor
nodes are battery-powered, and energy-efficient operations are important. To that end, before transmitting the final data to the central
station, remove redundancy from the collected data by neighbouring nodes is beneficial for sensors. Data aggregation is one of the
main strategies for reducing data redundancy and improving energy efficiency; it also extends the lifetime of wireless sensor networks.
Moreover, network traffic can be minimized by an efficient data aggregation protocol. It may be sensed by more than one sensor when
a particular target takes place in a particular area. This article provides an overview of different data aggregation methods and protocols,
taking into account the key problems and facets of data aggregation in wireless sensor networks. The structures of data aggregation are
grouped into four key classes, namely cluster-based, tree-based, chain-based and grid-based. The thorough comparison of the important
approaches of each class often gives a suggestion for more research.