Weathering the Reallocation Storm
Efficient service placement and workload allocation methods are necessary enablers for the actively studied topic of edge computing. In this paper, we […]
Opportunities of Federated Learning in Connected, Cooperative, and Automated Industrial Systems
Next-generation autonomous and networked industrial systems (i.e., robots, vehicles, drones) have driven advances in ultra-reliable low-laten-cy communications (URLLC) and computing. These networked […]
Revealing the Invisible With Model and Data Shrinking for Composite-Database Micro-Expression Recognition
Composite-database micro-expression recognition is attracting increasing attention as it is more practical for real-world applications. Though the composite database provides more sample […]
Distributed Federated Learning for Ultra-Reliable Low-Latency Vehicular Communications
In this paper, the problem of joint power and resource allocation (JPRA) for ultra-reliable low-latency communication (URLLC) in vehicular networks is studied. […]