Applying biological principles to designs of network services
Applied Soft Computing
BiSNET: A biologically-inspired middleware architecture for self-managing wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Robust artificial life via artificial programmed death
Artificial Intelligence
An In-Field-Maintenance Framework for Wireless Sensor Networks
DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
Computing the State of Specknets: Further Analysis of an Innate Immune-Inspired Model
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Exploiting malicious node detection for lifetime extension of sensor networks
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
Energy efficient route recovery methods for wireless sensor networks using hybrid checkpointing
ICCSA'07 Proceedings of the 2007 international conference on Computational science and Its applications - Volume Part II
Adaptive dynamic routing supporting service management for future internet
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
High Reliable In-Network Data Verification in Wireless Sensor Networks
Wireless Personal Communications: An International Journal
Journal of High Speed Networks
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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.