The internet-of-things (IoT) revolution is bringing millions of physical devices online (e.g. cars, UAVs, homes, medical devices), enabling them to connect to each other in real-time, as well as to cloud services. Wireless communication will be critical in providing IoT connectivity. There are three main strategic directions that are envisioned in the future wireless networking. First, enhanced mobile broadband will result in even larger data rates for future 3D applications such as virtual reality. Second, Smart City/Community applications require large number of sensors that communicate sporadically over large urban or rural areas in a scalable, asynchronous, and energy efficient manner. The previous two directions, while important, are not the focus of our proposal. Instead, our proposal focuses on low-latency and ultra-reliable communications and networking that is critical for latency-sensitive, closed-loop control applications, like vehicle to vehicle communications, collaborative swam planning, and industrial control. In such latency sensitive applications, we need to rethink the networking stack, coding, networking architecture, and control design to enable communications and networking that can provide ultra-low latency (99.999%). This is far beyond what is currently possible. But even more importantly, we do not know what is possible and what are the fundamental limits for control system design over low-latency, high-reliability communications.
In this proposal, we will be rethinking the scientific foundations for ultra-reliable, low-latency wireless communications for latency sensitive control applications. We propose to achieve our scientific agenda by addressing three intellectual challenges: 1) Low-latency channel coding, where the goal is to focus on short packet codes for control loops 2) Control over low latency-aware communication channels, where the goal is to understand the what is the optimal tradeoff of latency to reliability for control loops and 3) Learning for Large Scale Wireless Control Networks, where machine learning will perform resource allocation for large numbers of control loops with competing latency/reliability requirements We intend to evaluate the proposed research agenda by leveraging our existing Intel Science and Technology Center (ISTC) on Wireless Autonomous Systems and demonstrate our ideas in future wireless protocols (IEEE 802.11ax) and experimentally demonstrate it in high-speed V2V and fast formation control with aerial swarms. On the educational front, the University of Pennsylvania is planning to offer a Micro-Masters program in Internet of Things (IoT) on the edX MOOC platform. Longer term, our goal is to create a new community of researchers that focus on control over low-latency wireless networks for IoT devices. Towards this goal, we plan on leveraging departmental efforts to increase and diversify the PhD students working on this project.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
