Distributed allocation finds applications in many scenarios including CPU scheduling, distributed energy resource management, and networked coverage control. In this paper, we propose a fast convergent optimization algorithm with a tunable rate using the signum function. The convergence rate of the proposed algorithm can be managed by changing two parameters. We prove convergence over uniformly-connected multi-agent networks. Therefore, the solution converges even if the network loses connectivity at some finite time intervals. The proposed algorithm is all-time feasible, implying that at any termination time of the algorithm, the resource-demand feasibility holds. This is in contrast to asymptotic feasibility in many dual formulation solutions (e.g., ADMM) that meet resource-demand feasibility over time and asymptotically.

翻译：分布式分配在包括CPU调度、分布式能源资源管理和网络覆盖控制等多种场景中具有广泛应用。本文提出了一种利用符号函数且具有可调收敛速率的快速优化算法。通过调整两个参数，可控制该算法的收敛速度。我们证明了该算法在均匀连通多智能体网络上的收敛性，因此即使网络在有限时间区间内失去连通性，解仍能收敛。所提出的算法具备全时可行性，这意味着算法在任何终止时刻都能保证资源-需求可行性。这与许多对偶公式解法（如ADMM）的渐近可行性不同——后者的资源-需求可行性需随时间推移且渐近地实现。