The Impact of Data Aggregation Strategy on a Performance of Wireless Sensor Networks (WSNs)

Wireless Sensor Networks (WSNs) consist of small sensor devices whose main purpose is to detect phenomena in the target area. WSNs are now being used in a variety of essential applications. Data aggregation is an effective strategy in WSNs for best network performance. Because sensor networks have a high node density, similar data is sensed by numerous nodes, resulting in data redundancy which negatively affects the overall performance of the network. The data aggregation may be used to overcome this problem during packet routing from source nodes to the base station. From the recent literature, researchers are still having trouble finding an efficient and appropriate data aggregation method for WSNs. This paper provides insight and support for researchers by knowing how aggregation technology affects the performance of WSNs in the term of energy efficiency, accuracy, and latency after the applying data aggregation strategy. Also, two algorithms namely SOM and HAC were implemented using the Intel Berkeley Research Lab Dataset to show the impact of data aggregation on the overall performance of the WSNs through the results obtained.