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、种类和速度正在爆炸式增长，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。这项研究计划的目标，题为“分布式，安全，和基于事件的信号处理未来的网络物理系统”（DSEB-CPS）是研究有前途的想法在设计，开发和应用分布式信息融合技术，有助于鲁棒性，基于事件的，安全和自适应信号处理系统的进步。网络物理系统（CPS）是具有集成的计算和通信能力的工程系统，其通过网络空间与人类交互，并且最近出现在具有重要工程重要性的几个实际应用中，包括医疗系统、电力/能源网、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的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，如，安全的估计/控制协议，将多传感器信息跨多模态，管理资源（通信，计算，带宽和能源）的限制，并通过大量的相互作用的传感器收集的信息的合作融合。这样的研究议程在五个领域对传统信号处理提出了挑战：基于事件的传感、多模式/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。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。该研究计划试图提供四个交织的问题，即：（a）安全和基于事件的状态估计;（B）分布式估计/控制CPS;（c）大规模信号建模CPS，和（d）跨多个数据源的信息融合。 总之，本研究项目的智力价值是开发一个信号处理框架，用于分布式，安全和基于事件的信息采集，估计和CPS中的学习，并且由于能源，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.