Elimination of redundant data to enhance wireless sensor network performance using Multi level data aggregation technique
Rashmi Nagesh, Sarika Raga, Shakti Mishra · 2019
The WSN nodes are self configured to sense parameter like moisture, temperature, pressure, humidity, chemical content in an environment, The sensed data need to be handled efficiently to improve the network performance, therefore there is a need for data handling techniques or methods. Data handling methods like aggregation functions helps in removing redundant data which in turn reduces the traffic, congestion, and packet loss. Many data aggregation techniques aim at minimizing the network energy consumption which is suitable for small network [7]. Transmitting redundant data to the sink node brings down lifetime of the sensor nodes and also wastes of network resources. Therefore in this paper authors proposed an approach multi level data aggregation technique (MLDAT) which preprocess the sensor data to filter the raw data at different levels in the network to produce useful information or data for all size of network. The proposed approach also works for priority of the data which is requested by sending query to the target nodes. The sensor node from Texas instruments MSP430 have been considered in simulation as aggregator node for data aggregation. As a result the aggregator nodes unicast only the useful data towards sink node which reduces the latency, packet retransmission, effective utilization of the available bandwidth.