Distributed, Secure, and Event-based signal processing for future Cyber-Physical Systems

我们生活在一个数据泛滥的时代，数据的数量、种类和速度都在爆炸式增长，处理如此大量数据的能力有望限制流行病的传播，了解新兴社会计算系统的动态，并保护加拿大的关键基础设施。该研究项目名为“面向未来网络物理系统的分布式、安全和基于事件的信号处理”（DSEB-CPS），其目标是研究分布式信息融合技术的设计、开发和应用方面有前途的想法，这些技术有助于推进稳健、基于事件、安全和自适应的信号处理系统。网络物理系统（cps）是具有集成计算和通信能力的工程系统，通过网络空间与人类交互，最近出现在几个具有重要工程意义的实际应用中，包括医疗系统，电力/能源电网，航空航天，工业/制造过程控制和运输，其中执行安全和最佳状态估计是关键问题。******在cps背景下实现自适应和分布式信号处理系统需要解决关键的研究挑战，例如，估计/控制协议的安全性，跨多模态的多传感器信息的结合，管理资源（通信，计算，带宽和能量）约束，以及通过众多交互传感器收集的信息的协作融合。这样的研究议程在五个方面挑战了传统的信号处理：基于事件的传感、多模态/多传感器信号处理、信息融合、分散信号处理和安全估计/控制。适当的信号处理系统应该能够：以自适应和基于事件的方式提取相关信息，以创新和直观的方式协同估计物理系统的底层状态，适应不断变化的条件，并提供针对数据注入攻击的安全性。本研究计划试图为四个相互交织的问题提供答案，即：(a)安全和基于事件的状态估计；(b) cps的分布式估计/控制；(c) cps的大尺度信号模拟；(d)跨多个数据源的信息融合。*******总之，这个研究项目的智力价值在于为cps中的分布式、安全和基于事件的信息获取、估计和学习开发一个信号处理框架，因为能源、交通、医疗和工业cps是加拿大经济的关键驱动力，如果新知识和开发的技术被证明如我们所希望的那样有价值，预计它们将对我们的生活方式产生重大影响

We live in an era of data deluge, the volume, variety, and velocity of data is exploding and the ability to process such large amounts of data promises to limit the spread of epidemics, learn the dynamics of emergent social-computational systems, and also protect Canada's critical infrastructures. The objective of this research program, entitled "Distributed, Secure, and Event-based signal processing for future Cyber-Physical Systems", (DSEB-CPS) is to research promising ideas in the design, development and application of distributed information fusion technologies that contribute to the advancement of robust, event-based, secure and adaptive signal processing systems. Cyber-physical systems (CPSs) are engineering systems with integrated computational and communication capabilities that interact with humans through cyber space and have recently emerged in several practical applications of significant engineering importance including medical systems, power/energy grids, aerospace, industrial/manufacturing process control, and transportation, where performing secure and optimal state estimation is the key concern.******The realization of an adaptive and distributed signal processing system in the context of CPSs requires addressing key research challenges such as, security of the estimation/control protocols, incorporation of multi-sensor information across multi-modality, managing resource (communication, computation, bandwidth and energy) constraints, and cooperative fusion of information collected via a multitude of interacting sensors. Such a research agenda challenges traditional signal processing in five areas: event-based sensing, multimodal/multi-sensor signal processing, information fusion, decentralized signal processing, and secure estimation/control. The signal processing system in place should be able to: extract relevant information in an adaptive and event-based fashion, cooperatively estimate the underlying state of the physical system in innovative and intuitive ways, adapt to changing conditions, and offer security against data injection attacks. This research program attempts to provide answers to four interlaced problems, namely: (a) Secure and event-based state estimation; (b) Distributed estimation/control in CPSs; (c) Large-Scale Signal Modelling in CPSs, and; (d) Information Fusion Across Multitude of Data Sources. *******In conclusion, the intellectual merit of this research project is to develop a signal processing framework for distributed, secure and event-based information acquisition, estimation, and learning in CPSs and as energy, transportation, medical, and industrial CPSs are key drivers of Canada's economy, should the new knowledge and the developed technologies prove as valuable as we hope, it is expected that they will have significant impact on the way we live.**