A Centralized Mechanism to Make Predictions Based on Data From Multiple WSNs

In this work, we present a method that exploits a scenario with inter-Wireless Sensor Networks (WSNs) information exchange by making predictions and adapting the workload of a WSN according to their outcomes. We show the feasibility of an approach that intelligently utilizes information produced by other WSNs that may or not belong to the same administrative domain. To illustrate how the predictions using data from external WSNs can be utilized, a specific use-case is considered, where the operation of a WSN measuring relative humidity is optimized using the data obtained from a WSN measuring temperature. Based on a dedicated performance score, the simulation results show that this new approach can find the optimal operating point associated to the trade-off between energy consumption and quality of measurements. Moreover, we outline the additional challenges that need to be overcome, and draw conclusions to guide the future work in this field.Comment: 10 pages, simulation results and figures. Published i

Performance optimization of multiple interconnected heterogeneous sensor networks via collaborative information sharing

Interconnecting multiple sensor networks is a relatively new research field which has emerged in the Wireless Sensor Network domain. Wireless Sensor Networks (WSNs) have typically been seen as logically separate, and few works have considered interconnection and interaction between them. Interconnecting multiple heterogeneous sensor networks therefore opens up a new field besides more traditional research on, e.g., routing, self organization, or MAC layer development. Up to now, some approaches have been proposed for interconnecting multiple sensor networks with goals like information sharing or monitoring multiple sensor networks. In this paper, we propose to utilize inter-WSN communication to enable Collaborative Performance Optimization, i.e., our approach aims to optimize the performance of individual WSNs by taking into account measured information from others. The parameters to be optimized are energy consumption on the one hand and sensing quality on the other.This work has been partially supported by the Spanish Government under projects TEC2008-06055 (Plan Nacional I+D), CSD2008-00010 (ConsoliderIngenio Program) and by the Catalan Government (SGR2009#00617)