A DISTRIBUTED ADMM-LIKE METHOD FOR RESOURCE SHARING OVER TIME-VARYING NETWORKS
A DISTRIBUTED ADMM-LIKE METHOD FOR RESOURCE SHARING OVER TIME-VARYING NETWORKS
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DOI：
10.1137/17m1151973
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发表时间：
2019-01-01
影响因子：
3.1
通讯作者：
Hamedani, Erfan Yazdandoost
中科院分区：
文献类型：
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作者：
Aybat, Necdet Serhat;Hamedani, Erfan Yazdandoost
我们考虑时变通信网络上的协作多代理资源共享问题，其中仅允许本地通信。目标是最小化受耦合代理决策的二次曲线约束的特定代理复合凸函数的总和。我们提出了一种分布式原对偶算法 DPDA-D，来解决时变（无向）定向通信网络上共享问题的鞍点公式；我们证明了原始-对偶迭代序列收敛到由原始最优解和耦合约束的一致对偶价格定义的点。此外，我们还提供了代理双重价格评估的次优性、不可行性和共识违反的收敛率；检查底层网络拓扑对所提出的去中心化算法收敛速度的影响；并在基础追求去噪和多通道功率分配问题上将DPDA-D与集中式方法进行比较。
We consider cooperative multiagent resource sharing problems over time-varying communication networks, where only local communications are allowed. The objective is to minimize the sum of agent-specific composite convex functions subject to a conic constraint that couples agents' decisions. We propose a distributed primal-dual algorithm, DPDA-D, to solve the saddle-point formulation of the sharing problem on time-varying (un)directed communication networks; and we show that the primal-dual iterate sequence converges to a point defined by a primal optimal solution and a consensual dual price for the coupling constraint. Furthermore, we provide convergence rates for suboptimality, infeasibility, and consensus violation of agents' dual price assessments; examine the effect of underlying network topology on the convergence rates of the proposed decentralized algorithm; and compare DPDA-D with centralized methods on the basis pursuit denoising and multichannel power allocation problems.