Sensor data aggregation for resource inventory applications

TLDR: This work proposes a novel data aggregation strategy and algorithms to obtain the population of the objects to be sensed in the networks and suggests more profoundly that there is yet design space to explore in application-specific data aggregation for energy conservation.

Abstract: With the creative use of sensors, in the future, sensor networks could impact on a wide variety of applications from national security to consumer electronics. Sharing the vision and emphasizing the energy efficiency of data dissemination for resource inventory applications, we propose a novel data aggregation strategy and algorithms to obtain the population of the objects (i.e., the resource) to be sensed in the networks. With a set of cautiously validated simulations, we show that the energy consumption in applying our solution is only one third of the original case and scalable to the object population. Experimental results also show that we are able to obtain consistent lower and upper bounds at 70% and 180% of the exact population. While we show the solution works effectively for resource inventory applications, this work suggests more profoundly that there is yet design space to explore in application-specific data aggregation for energy conservation.