Data Aggregation Techniques in Wireless Sensors Networks: A survey

The rapid growth in Internet of Things IoT applications has increased the demand for Wireless Sensor Network (WSN) as an essential supportive Ad-hoc network class in the IoT stack. However, managing the network lifetime related to power consumption and network capacity is still a significant challenge that affects WSN functionality. Wireless network capacity is primarily affected by available bandwidth, error rate, and Signal to Noise Ratio (SNR). These factors have more profound effects on WSN because of limitations in power supplies and the ad-hoc mode implemented in WSN. Hence, it is essential to maintain the network lifetime and capacity to use WSN in real-world IoT applications. Data aggregation techniques with efficiently collecting and aggregating packets will help to reduce power consumption and reduce network traffic congestions.This study aims to systematically analyze and review the data aggregation techniques used in WSN. The paper presents a comprehensive survey based on the current work, component classification, and evaluation table. Additionally, an analysis based on the data aggregation technique is conducted for improving the network capacity based on the existing technologies. Also, the study proposes an aggregation framework based on the literature study, identifying the significant components used for obtaining an enhanced solution for improving network capacity in a WSN with the help of the data aggregation technique.