Title: Distributed Allocation and Resource Scheduling Algorithms Resilient to Link Failure Show Chinese title

Title: 分布式分配和资源调度算法对链路故障的弹性

Abstract: Distributed resource allocation (DRA) is fundamental to modern networked systems, spanning applications from economic dispatch in smart grids to CPU scheduling in data centers. Conventional DRA approaches require reliable communication, yet real-world networks frequently suffer from link failures, packet drops, and communication delays due to environmental conditions, network congestion, and security threats. We introduce a novel resilient DRA algorithm that addresses these critical challenges, and our main contributions are as follows: (1) guaranteed constraint feasibility at all times, ensuring resource-demand balance even during algorithm termination or network disruption; (2) robust convergence despite sector-bound nonlinearities at nodes/links, accommodating practical constraints like quantization and saturation; and (3) optimal performance under merely uniformly-connected networks, eliminating the need for continuous connectivity. Unlike existing approaches that require persistent network connectivity and provide only asymptotic feasibility, our graph-theoretic solution leverages network percolation theory to maintain performance during intermittent disconnections. This makes it particularly valuable for mobile multi-agent systems where nodes frequently move out of communication range. Theoretical analysis and simulations demonstrate that our algorithm converges to optimal solutions despite heterogeneous time delays and substantial link failures, significantly advancing the reliability of distributed resource allocation in practical network environments. Show Chinese abstract

Abstract: 分布式资源分配（DRA）是现代网络化系统的基础，其应用范围从智能电网中的经济调度到数据中心的CPU调度。传统的DRA方法需要可靠的通信，然而现实世界的网络经常由于环境条件、网络拥塞和安全威胁而遭受链路故障、数据包丢失和通信延迟。我们引入了一种新的弹性DRA算法，以解决这些关键挑战，我们的主要贡献如下：（1）在任何时候都保证约束可行性，确保在算法终止或网络中断期间资源需求平衡；（2）即使在节点/链路上存在区间边界非线性，也能实现鲁棒收敛，适应量化和饱和等实际约束；（3）在仅需均匀连接网络的情况下实现最优性能，消除了对连续连接的需求。与现有方法不同，我们的图论解决方案利用网络渗透理论，在间歇性断开期间保持性能。这使其特别适用于移动多智能体系统，其中节点经常移动出通信范围。理论分析和仿真表明，即使存在异构时间延迟和大量链路故障，我们的算法也能收敛到最优解，显著提高了实际网络环境中分布式资源分配的可靠性。