In-network processing and data-aggregation are key features of Wireless Sensor Networks. In fact, they allow the data to be processed and aggregated as they go through the network. In this work, we propose an innovative congestion control algorithm for wireless sensor networks based on data aggregation, which will be referred to as Data-Aggregation Congestion Control (DACC). The algorithm has been designed by exploiting linear discrete time control theory. It can be applied in a fully distributed way. Using our approach, each node periodically evaluates the amount of data to aggregate in order to control the level of its transmission queue. The aggregation process involves only linear operations and allows the sink node to estimate the confidence level of received data. The effectiveness of DACC has been evaluated with reference to a temperature monitoring problem in a fire detection scenario, using the Castalia simulator. Results have shown that DACC is able to significantly improve the estimation accuracy.
Congestion control based on data-aggregation for wireless sensor networks / Mastrocristino, T.; Tesoriere, G.; Grieco, Luigi Alfredo; Boggia, Gennaro; Palattella, M. R.; Camarda, Pietro. - (2010), pp. 3386-3391. (Intervento presentato al convegno IEEE International Symposium on Industrial Electronics, ISIE 2010 tenutosi a Bari, Italy nel July 4-7, 2010) [10.1109/ISIE.2010.5635478].
Congestion control based on data-aggregation for wireless sensor networks
GRIECO, Luigi Alfredo;BOGGIA, Gennaro;CAMARDA, Pietro
2010-01-01
Abstract
In-network processing and data-aggregation are key features of Wireless Sensor Networks. In fact, they allow the data to be processed and aggregated as they go through the network. In this work, we propose an innovative congestion control algorithm for wireless sensor networks based on data aggregation, which will be referred to as Data-Aggregation Congestion Control (DACC). The algorithm has been designed by exploiting linear discrete time control theory. It can be applied in a fully distributed way. Using our approach, each node periodically evaluates the amount of data to aggregate in order to control the level of its transmission queue. The aggregation process involves only linear operations and allows the sink node to estimate the confidence level of received data. The effectiveness of DACC has been evaluated with reference to a temperature monitoring problem in a fire detection scenario, using the Castalia simulator. Results have shown that DACC is able to significantly improve the estimation accuracy.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
