论文标题
算法解决分布式共识的优化和分布式资源分配的互惠性
Reciprocity of Algorithms Solving Distributed Consensus-Based Optimization and Distributed Resource Allocation
论文作者
论文摘要
本文旨在提出一个程序，以通过使用分布式算法进行网络资源分配的分布式算法来得出分布式算法，以进行基于分布式共识的优化，而使用/没有同步协议的切换网络，反之亦然。结果表明，基于一阶分布式分布式优化算法可用于在弱假设下与同步协议的分布式资源分配的最佳解决方案，而不是文献中的非转换（静态）网络的假设。结果表明，一阶分布式资源分配算法可用于寻找基于分布式共识的优化的最佳解决方案。此处介绍的结果可以应用于具有或没有同步协议的时间变化和随机定向网络，并具有任意初始化。结果，现在可以使用几种算法来得出基于共识的优化和资源分配的分布式算法，这些算法可以克服现有结果的局限性。虽然本文的重点是一阶梯度算法，但要注意的是，结果也可与二阶梯度算法一起使用。
This paper aims at proposing a procedure to derive distributed algorithms for distributed consensus-based optimization by using distributed algorithms for network resource allocation and vice versa over switching networks with/without synchronous protocol. It is shown that first-order gradient distributed consensus-based optimization algorithms can be used for finding an optimal solution of distributed resource allocation with synchronous protocol under weaker assumptions than those given in the literature for non-switching (static) networks. It is shown that first-order gradient distributed resource allocation algorithms can be utilized for finding an optimal solution of distributed consensus-based optimization. The results presented here can be applied to time-varying and random directed networks with or without synchronous protocol with arbitrary initialization. As a result, several algorithms can now be used to derive distributed algorithms for both consensus-based optimization and resource allocation, that can overcome limitations of the existing results. While the focus of this paper is on the first-order gradient algorithms, it is to be noted that the results also work with second-order gradient algorithms.
