The flavor of the research in our group is one that mixes experiments with theories. We like to look for interesting and practically relevant theoretical problems to solve from our experimental results.
Industrial Wireless Network for IIoT
Real-Time Time-slotted System on SDR (RTTS-SDR)
RTTS-SDR is a system that we implemented on PC-USRP using GNURadio. It can achieve synchronization among nodes and aligned their time slots to within 100ns, and the end-to-end latency can be down to 3.75ms.
A Just-In-Time Networking Framework for Minimizing Request-Response Latency of Wireless Time-Sensitive Applications
This project puts forth a networking paradigm, referred to as just-in-time (JIT) communication, to support client-server applications with stringent request-response latency requirement. Of interest is not just the round-trip delay of the network, but the actual request-response latency experienced by the application.
Physical-layer Network Coding (PNC)
PNC is about applying the principle of NC by allowing EM waves to add up physically in a wireless broadcast situation. we provide a real-time implemnetation of PNC in this project. Details of the Source code of RPNC can be found in the project page.
Networking for Blockchain
Speeding up Block Propagation in Bitcoin Network: Uncoded and Coded Designs
In this work, we redesign the current Bitcoin’s networking protocol to increase TPS without changing vital components in its consensus-building protocol. In particular, we improve the compact-block relaying protocol to enable the propagation of blocks containing a massive number of transactions without inducing extra propagation latencies. Our improvements consist of (i) replacing the existing store-and-forward compact-block relaying scheme with a cut-through compact-block relaying scheme; (ii) exploiting rateless erasure codes for P2P networks to increase block-propagation efficiency.
AI-driven Wireless Networking
Uncertainty-of-information Scheduling
AoI is motivated by the fact that in many modern communications and control systems, particularly those used to support remote industrial processes, automation, and IoT applications, what fundamentally matters is not throughput or delay; instead, it is the freshness of information collected from the remote processes that counts. Importantly, AoI as a performance measure is related to, but yet distinct from, the low latency requirement in 5G Ultra-Reliable Low Latency Communication (URLLC) . For AoI, the rate at which the information from the remote process ages also matters, not just the latency induced by the communication system.
UoI, the performance metric of focus in this project, is a twist to AoI. We argue that the freshness of information is not necessarily related to the age of the information, just like some food goes stale quickly while other food remains fresh for a long time. If we know the “coherence time” of the remote processes, we can make better decisions on when to collect information from them, allowing efficient utilization of the underlying communication and computing resources to ensure the freshness of information at a monitoring center.