Emergent strategies to optimise collaborative transmission schemes

• Antragsteller: Professor Dr. Michael Beigl
• Fachliche Zuordnung: Sicherheit und Verlässlichkeit, Betriebs-, Kommunikations- und verteilte Systeme
• Förderung: Förderung von 2009 bis 2012
• Projektkennung: Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 133877679

Cooperative and collaborative strategies for transmission in wireless sensor networks enable transmission range restricted nodes to reach distant receivers by superimposing transmission signals. This addresses an important practical problem of wireless sensor networks. In this proposal we extend this strategy by emergent properties: We establish a method to adapt the collaborative emergent optimisation process by a) remembering previous behaviour from similar situations, b) using this information to adapt the current optimisation run by using randomised and feedbackbased approaches to determine an optimally pre-synchronised set of nodes for transmission and c) optimising and learning observed optimisation behaviour for the random process, which is better than the behaviour we had in memory so far. Using feedback information is a natural and intuitive approach to adapt to the the scenario's dynamics without the requirement for external intervention. Our approach will therefore show both emergent and self-organisation properties. We will demonstrate the suitability of the method by implementing and deploying a sensor network with 100 nodes in an setting, and testing this also in an agriculture setting. The demonstration will show how to globally minimise and equalise the energy used for collaborative transmission.

• DFG-Verfahren: Schwerpunktprogramme
• Teilprojekt zu: SPP 1183: Organic Computing