Assistant Professor of Computer Science Marco Levorato was awarded $415,000 from the National Science Foundation (NSF) for his grant, “Reliable Task Offloading in Mobile Autonomous Systems Through Semantic MU-MIMO Control.”
“Mobile autonomous systems (MASs) such as self-driving vehicles and drones have a pivotal role in critical applications such as urban mobility, precision agriculture and remote surveillance,” explains the grant abstract. “To achieve their tasks, MASs increasingly rely on high-throughput low-latency streaming of computer vision tasks (e.g., object detection) to edge servers. However, ephemeral environmental factors such as blockages, congestion and fading may erratically interrupt the flow of tasks to the edge servers.”
This project aims to develop applications that are “resilient by design” without compromising task accuracy. The three-year project is a collaboration with Francesco Restuccia, assistant professor of electrical and computer engineering at Northeastern University.
“I partnered with Francesco as he is a lead expert in wireless systems,” says Levorato, “and has access (and expertise to use) the large-scale wireless testbed (Colosseum, funded by NSF) at Northeastern.”
The researchers will be developing a drone-based prototype and performing large-scale data collection campaigns at Northeastern. They will also use a drone experimental testbed at UC Irvine to collect wireless/multimedia data to train the algorithms and to perform extensive testing and performance evaluation.
The core goal of this project, as outlined in the abstract, is to design and evaluate “novel techniques for hardware-based semantic-driven joint optimization of multimedia compression strategies and MU-MIMO [Multi-User Multiple-Input and Multiple-Output] transmissions in the context of resource-limited wireless systems.”
— Shani Murray