Exploiting Mobility-assisted Collaboration for Adaptive Aquatic Sensor Networks

本研究的目的是为由资源有限的节点组成的水生传感器网络的设计和运行建立一个原则性框架。提出的方法是利用节点之间的自适应和协作来整体处理甚至利用感知、通信和移动性中的不确定性。主要研究内容包括动态环境的在线传感器和融合校准，模型驱动的无线电功率自适应以实现有保证的通信性能，以及在感知、组网和控制的联合优化中利用节点的移动性和流体运动来实现有效的覆盖和跟踪。所提出的方法将在密歇根州立大学凯洛格生物站使用机器鱼网络检测和跟踪有害藻华的情况下得到验证。该项目将产生一个统一的水生传感器网络设计框架，以实现节能运行和保证的时空传感性能。该项目开发的一些方法，例如利用看似不受欢迎的环境干扰，可以应用于航空和陆地传感器网络，从而使这些领域也受益。该项目预计将使水生传感器网络更接近其设想的应用，并对湖泊和其他生态系统的监测、石油泄漏和污染物的跟踪以及港口和河流的监测产生积极影响。该项目将丰富两门研究生水平的课程，并为研究生和本科生提供跨学科培训。该项目还将提供一个极好的机会，通过互动讲座、机器鱼比赛和参加密歇根州立大学的教师培训计划来接触K-12学生和学校。

The objective of this research is to establish a principled framework for the design and operation of aquatic sensor networks consisting of resource-limited nodes. The proposed approach is to exploit adaptation and collaboration among nodes to holistically deal with or even leverage uncertainties in sensing, communication, and mobility. Main research thrusts include online sensor and fusion calibration for dynamic environments, model-driven radio power adaptation to achieve assured communication performance, and exploitation of node mobility and fluid motion in the joint optimization of sensing, networking, and control to realize efficient coverage and tracking. The proposed methodology will be validated in detection and tracking of harmful algal blooms at the MSU Kellogg Biological Station using networks of robotic fish.The project will result in a unifying design framework for aquatic sensor networks to achieve energy-efficient operation with assured spatiotemporal sensing performance. Some methodologies developed in this project, e.g., exploiting the seemingly undesirable environmental disturbances, could apply to aerial and terrestrial sensor networks and thus benefit those fields as well.The project is expected to bring aquatic sensor networks much closer to their envisioned applications, and positively impact monitoring of lakes and other ecosystems, tracking of oil spills and pollutants, and surveillance of ports and rivers. The project will enrich two graduate-level courses and provide interdisciplinary training for graduate and undergraduate students. The project will also offer an excellent opportunity to reach out to K-12 students and schools through interactive lectures, robotic fish competitions, and participation in a teacher training program at MSU.