Self-Organized Event Detection in Sensor Networks using Bio-inspired Promoters and Inhibitors

Sensor and Actor Networks (SANETs) represent a specific category of massively distributed systems in which coordination and control of the participating networked nodes is especially challenging. Recently, a number of self-organization methods have been published that focus on network-centric operation in such networks. Rule-based Sensor Network (RSN) is a programming approach that supports this kind of operation. It mainly features inherent support for heterogeneous nodes. Until now, the rule execution in RSN is too static for application in highly dynamic environments such as event detection of mobile targets. We present a bioinspired approach for adaptation of the local rule execution, which is based on an promoter / inhibitor scheme. The application of this biological technique leads to improved reactivity and resource utilization. The advantages are demonstrated based on a comprehensive simulation study.