EAGER: Multi-Agent Network Control for Adaptive Sensing and Monitoring in Wireless Sensor Networks

这个探索性研究（EAGER）项目的目标是探索无线传感器网络中自适应传感和监测的一些新想法。重点将放在制定受自然免疫系统和代理技术启发的监测方法上，这可能会导致自适应传感和监测。为了模拟适应性免疫反应，将研究免疫细胞协作的数学模型，并为无线监测网络中这种机制的设计提供指导。该项目将寻找一个基于代理的网络框架，以实现免疫启发的自适应、自组织和自主异常检测。将研究多目标优化算法对智能体生成和分布的鲁棒控制，以提高系统响应能力、异常检测概率和网络寿命。基于免疫网络理论的算法也将被研究用于无监督异常检测。本课题的成功完成将对当前的自适应传感与监测能力产生重大影响。预期的适应性免疫反应模型可能允许监测系统根据监测条件的变化调整监测剂的数量和类型。多目标代理生成和分发策略可以在响应性、异常检测概率和网络生命周期之间提供良好的平衡。基于免疫网络的异常检测可以根据环境和操作的变化提供名义行为模型的动态更新。该项目的成果将在推进关键基础设施、电网、交通系统和军事应用的监测技术方面提供明显的社会效益。研究成果将通过以下机制广泛传播：网络、论文出版、专业讲座和将材料纳入教学。大学预科生、本科生和研究生的教育机会贯穿于整个研究项目。推广工作将影响农村、低收入和大学预科生。

The objective of this EArly-concept Grants for Exploratory Research (EAGER) project is to explore some novel ideas on adaptive sensing and monitoring in wireless sensor networks. The focus will be on formulating monitoring methodology inspired by the natural immune system and agent technology, which could potentially lead to adaptive sensing and monitoring. To mimic adaptive immune response, mathematical models will be investigated to study the collaboration of immune cells and provide guideline for the design of such mechanisms in wireless monitoring networks. The project will look for an agent-based network framework to enable immune-inspired adaptive, self-organizing, and autonomous anomaly detection. Multi-objective optimization algorithms will be studied for the robust control of agent generation and distribution to enhance system responsiveness, anomaly detection probability, and network lifetime. Immune-network-theory-based algorithms will also be investigated for the unsupervised anomaly detection.The successful completion of this research project will have a great impact on the current ability of adaptive sensing and monitoring. The anticipated adaptive immune response models could potentially allow a monitoring system to adjust the number and type of monitoring agents in response to the changes in monitoring conditions. Multi-objective agent generation and distribution strategies could provide a good balance across responsiveness, anomaly detection probability, and network lifetime. The immune-network-based anomaly detection could offer dynamic updates of a nominal behavior model due to environmental and operational changes. The outcomes of this project will offer clear societal benefits in advancing monitoring technologies for critical infrastructure, power grids, traffic systems, and military applications. The research results will be widely disseminated via the following mechanisms: Web, publication of papers, professional talks, and by incorporating materials into teaching. Educational opportunities for pre-college, undergraduate, and graduate students are integrated throughout the research program. The outreach efforts will impact rural, low income, and pre-college students.