arXiv · 2508.02164
Distributed Constraint-coupled Resource Allocation: Anytime Feasibility and Violation Robustness
Abstract
This paper considers distributed resource allocation problems (DRAPs) with a coupled constraint for real-time systems. Based on primal-dual methods, we adopt a control perspective for optimization algorithm design by synthesizing a safe feedback controller using control barrier functions to enforce constraint satisfaction. On this basis, a distributed anytime-feasible resource allocation (DanyRA) algorithm is proposed. It is shown that DanyRA algorithm converges to the exact optimal solution of DRAPs while ensuring feasibility of the coupled inequality constraint at all time steps. Considering constraint violation arises from potential external interferences, a virtual queue with minimum buffer is incorporated to restore the constraint satisfaction before the pre-defined deadlines. We characterize the trade-off between convergence accuracy and violation robustness for maintaining or recovering feasibility. DanyRA algorithm is further extended to address DRAPs with a coupled equality constraint, and its linear convergence rate is theoretically established. Finally, a numerical example is provided for verification.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Wenwen Wu, Shanying Zhu, Cailian Chen, Xinping Guan. 2025-08-04. Distributed Constraint-coupled Resource Allocation: Anytime Feasibility and Violation Robustness. https://arxiv.org/abs/2508.02164
Cite the original work for its findings. Save a collection to share your selection of sources.