SASHA: toward a self-healing hybrid sensor network architecture

For widespread adoption of sensor technology, robustness in the event of abnormal behavior, such as a network intrusion or failures of components or nodes, is critical. Current research on robust and resilient sensor networking is focused on specific tasks - secure broadcast, secure aggregation, secure localization or fault-tolerant feature extraction. While these primitives provide useful functionality, what has been lacking is a comprehensive, holistic approach to sensor network robustness across various failure modalities. We propose a self-healing hybrid sensor network architecture, called SASHA, that is inspired by and coopts several mechanisms used by the acquired natural immune system to attain its autonomy, robustness, diversity and adaptability to unknown pathogens, and compactness. SASHA encompasses automatic fault recognition and response over a wide range of possible faults. Moreover, it is an adaptive architecture that can learn and evolve its monitoring and inference capabilities over time to deal with unknown faults. We illustrate the workings of SASHA using the example of fault-tolerant sensor data collection and outline an agenda for future research.