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

EAGER：BISON：用于稳健无线传感器网络的仿生解决方案

• 批准号: 1355505
• 负责人: Sajal Das
• 金额: $ 10万
• 依托单位: Missouri University of Science and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1355505&HistoricalAwards=false
• 关键词: EAGER; BISON; Bio; Inspired; Solutions

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.

通过数十亿年的“适者生存”算法的“计算”，生物系统自然变得强大，并能自适应环境变化，如扰动和不利情况。受这一现象的启发，这个雄心勃勃的EAGER项目被称为BISON，旨在通过利用自然计算的最佳结果来设计强大的无线传感器网络（wsn）。生物体的功能稳健性通常归因于基因调控网络（grn）的优化拓扑结构，该网络通过基因之间的信号传递来监督生物细胞的适当行为。grn能适应动态变化（如噪声和扰动），也能适应节点的移除或故障。认识到WSNs在概念上在类似的条件下运行，BISON项目将利用GRNs的内在特征来提高WSNs的效率和鲁棒性。这个探索性项目将：(i)通过将grn和WSN建模为图来建立grn和WSN之间的创新映射，以及（ii）在grn中应用生物启发的鲁棒模板来设计弹性和传输效率高的WSN拓扑。从生物学原理出发，将导致无线传感器网络稳健设计的新范式转变，应用于环境和健康监测、入侵检测和目标跟踪，以及网络物理系统的脆弱性分析。提出的基本方法将在了解其信息传输鲁棒性的统一目标下，对来自不同生物的GRN拓扑进行比较，从而产生新的研究。BISON项目旨在超越生物网络和健壮的WSNs之间的映射到其他网络，如无线蜂窝网络，车辆和社会网络。研究成果将被整合到密苏里科技大学现有的计算机科学课程中，例如传感器网络的进展和无线网络的基础知识，从而在跨学科的主题中培养不同的学生。还将努力招收女性和少数民族学生，并让本科生参与生物启发的应用。研究成果将通过专门的网站、高质量会议和期刊上的出版物和演讲，以及由PI共同创立的复杂网络动力学（CoNeD）研讨会进行传播。