Energy efficient handling of big data in embedded, wireless sensor networks

The development of wireless sensor networks has reached a point where each individual node of a network may store and deliver a massive amount of (sensor-based) information at once or over time. In the future, massively connected, highly dynamic wireless sensor networks such as vehicle-2-vehicle communication scenarios may hold an even greater information potential. This is mostly due to the increase in node complexity. Consequently, data volumes will become a problem for traditional data aggregation strategies traffic-wise as well as with regard to energy efficiency. Therefore, in this paper we suggest to call such scenarios big data scenarios as they pose similar questions and problems as traditional big data scenarios. Although the latter focus mostly on business intelligence problems. We then propose an aggregation strategy tied to technological prerequisites which enables the efficient use of energy and the handling of large data volumes. Furthermore, we demonstrate the energy conservation potential based on experiments with actual sensor platforms.