应网络与交换技术国家重点实验室和泛网无线通信教育部重点实验室的邀请，美国德州农工大学（Texas A&M University）Shuguang (Robert) Cui教授于2015年6月5日访问我校并作学术报告。
报告题目：Networked Large-ScaleSensing over Complex Systems
主讲人：Prof. Shuguang (Robert) Cui（Fellow，IEEE）
Abstract: Data intelligence is the core building block for any modern and future cyber-physical systems, and it involves three major aspects: data processing, data storage, and data communication. Interesting and challenging research problems could be formulated over the interactions among the above three aspects in the context of cyber-physical systems. In this talk, we focus on one such interaction between data processing and data communication, to solve a specific problem on networked large-scalesensing, where data processing has to be performed in a distributed fashion over a communication network. In particular, we seek good estimates of the randomly-varying state process in a dynamic cyber-physical system, at multiple distributed sensing nodes, each of them only having a partial observation of the overall state. We allow nodes to talk with neighbors defined over a communication graph, where we introduce a communication rate constraint on the average number of message exchanges allowed across the network per unit time. In a distributed Kalman filtering framework, we establish the consensus result to show that the respective error variance at each distributed node converges weakly in distribution. In addition, with large deviation analysis, we could show that such a distribution collapses to a Dirac measure (i.e., the error performance achieved by the ideal centralized Kalman filter) exponentially fast as we increase the network communication rate. To further satisfy more practical communication requirements, we then extend the result to the case with quantized message exchanges, with similar convergence results established. Towards the end of the talk, I will briefly mention another result on the interaction between data storage and data communication.