  In this paper, we investigate a key problem of Internet of Things (IoT)
applications in practice. Our research objective is to optimize the
transmission frequencies for a group of IoT edge devices under practical
constraints. Our key assumption is that different IoT devices may have
different priority levels when transmitting data in a resource-constrained
environment and that those priority levels may only be locally defined and
accessible by edge devices for privacy concerns. To address this problem, we
leverage the well-known Alternating Direction Method of Multipliers (ADMM)
optimization method and demonstrate its applicability for effectively managing
various IoT data streams in a decentralized framework. Our experimental results
show that the transmission frequency of each edge device can converge to
optimality with little delay using ADMM, and the proposed system can be
adjusted dynamically when a new device connects to the system. In addition, we
also introduce an anomaly detection mechanism to the system when a device's
transmission frequency may be compromised by external manipulation, showing
that the proposed system is robust and secure for various IoT applications.
