EAGER: BISON: Bio-Inspired Solutions for RobustWireless Sensor Networking

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Through billions of years 'computation' using 'survival of the fittest' algorithm, biological systems have naturally become robust and self-adaptive to environmental changes, such as perturbations and adverse situations. Inspired by this phenomenon, this ambitious EAGER project, called BISON, will aim to design robust wireless sensor networks (WSNs), by leveraging optimal results from nature's computation. Functional robustness of living organisms is often attributed to the optimized topological structures of gene regulatory networks (GRNs) that oversee proper behavior of biological cells by means of signal transmissions between the genes. GRNs are adaptive to dynamic changes (e.g., noises and perturbations) and also resilient to the removal or malfunction of nodes. Recognizing that WSNs conceptually operate under similar conditions, the BISON project will exploit intrinsic features of GRNs to improve efficiency and robustness of WSNs.This exploratory project will: (i) establish innovative mapping between GRNs and WSNs by modeling them as graphs, and (ii) apply bio-inspired robust templates in GRNs to design resilient and transmission-efficient WSN topologies. Approaching from biological principles will lead to a novel paradigm shift in robust design of wireless sensor networks with applications in environmental and health monitoring, intrusion detection and target tracking, and vulnerability analysis of cyber-physical systems. The proposed fundamental approach will produce new research in comparing GRN topologies from different organisms under the unifying goal of understanding their information transport robustness.The BISON project aims to transcend the mapping between biological networks and robust WSNs to other networks such as wireless cellular networks, vehicular and social networks. Research findings will be integrated into existing computer science courses, such as advances in sensor networks and fundamentals of wireless networks, at the Missouri University of Science and Technology, thus training diverse students in an interdisciplinary topic. Efforts will also be made to recruit women and minority students, and engage undergraduates to bio-inspired applications. Research outcomes will be disseminated through a dedicated website, publications and presentations in high quality conferences and journals, and through the Complex Networks Dynamics (CoNeD) workshop co-founded by the PI.