Time-critical instantiations of wireless networks such as vehicular networks, robotic systems, real-time surveillance, and networked control require stringent deadline requirements on packet transmissions. These emerging networks demand reliable and predictable transmissions over an unreliable, time-varying wireless medium to support applications such as warning messages, voice calls and video streaming. Despite remarkable progress in the design of wireless networks with maximum throughput and low delays over the last two decades, communications with hard deadlines in wireless networks remains a challenging open problem. Most existing works on delay performance in wireless networks focus on reducing average delays rather than guaranteeing hard deadlines. The goal of this project is to develop fundamental theories and distributed algorithms for transmitting packets with hard deadlines in wireless networks for time-critical applications. Technical advances in this project will contribute to the improvement of wireless systems for time-critical communications, including the so-called internet of things, cyber-physical systems, emergency response wireless networks, and sensor networks.
The problem of supporting communications with hard deadlines in ad hoc wireless networks is very challenging because the capacity region of the network is arrival-dependent, and packet deadlines induce special types of spatial and temporal correlation. This project focuses on a comprehensive resource allocation solution for time-critical communications in wireless networks by utilizing the following four novel techniques: (1) a virtual link approach to achieve spatial-temporal resource allocation to guarantee end-to-end hard deadlines, (2) a deadline-aware random access algorithm, (3) a virtual frame approach to deal with the infinite temporal correlation among packets, and (4) deadline-aware PHY/MAC resource allocation. By exploiting these transformative technical approaches, the project will (1) design distributed algorithms for mission-critical wireless networks, (2) design resource allocation algorithms for supporting hard end-to-end deadlines for physical layer models beyond the collision model and (3) design joint routing/scheduling algorithms for multihop traffic flows with end-to-end deadline constraints. Education is a core component of this project. During the course of this project, research and education will be integrated by including new theories and algorithms developed in this project into graduate-level courses. Every effort will be made to involve undergraduates and students from under-represented students in this project.
