On the throughput maximization of sensor networks using data aggregation and reduction

Researchers have proposed aggregation models for Wireless Sensor odes (WS ). These models allow the sampling of data at the sensor nodes' internal memory. The aggregated data is transmitted to the sink node when some predefined conditions are fulfilled. It is very likely that monitored data samples may remain unchanged for significant time depending upon the environmental conditions being monitored. This paper suggests a data reduction algorithm which exploits the non-variability in the aggregated data samples at the sensor nodes. The proposed data reduction algorithm allows the accommodation of more information such as video data in WS packets. The throughput of such kind of wireless sensor network is investigated in this paper. Results show that the data aggregation and reduction can increase the maximum throughput of WS.