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Analysis of distributed ADMM algorithm for consensus optimisation over lossy networks

Majzoobi, Layla and Shah-Mansouri, Vahid and Lahouti, Farshad (2018) Analysis of distributed ADMM algorithm for consensus optimisation over lossy networks. IET Signal Processing, 12 (6). pp. 786-794. ISSN 1751-9675. doi:10.1049/iet-spr.2018.0033.

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Alternating direction method of multipliers (ADMM) is a popular convex optimisation algorithm, which is implemented in a distributed manner. Applying this algorithm to consensus optimisation problem, where a number of agents cooperatively try to solve an optimisation problem using locally available data, leads to a fully distributed algorithm which relies on local computations and communication between neighbours. In this study, the authors analyse the convergence of the distributed ADMM algorithm for solving a consensus optimisation problem over a lossy network, whose links are subject to failure. They present and analyse two different distributed ADMM-based algorithms. The algorithms are different in their network connectivity, storage and computational resource requirements. The first one converges over a sequence of networks which are not the same but remains connected over all iterations. The second algorithm is convergent over a sequence of different networks whose union is connected. The former algorithm, compared to the latter, has lower computational complexity and storage requirements. Numerical experiments confirm the proposed theoretical analysis.

Item Type:Article
Related URLs:
URLURL TypeDescription
Majzoobi, Layla0000-0002-2890-6694
Shah-Mansouri, Vahid0000-0003-4810-491X
Lahouti, Farshad0000-0002-8729-873X
Additional Information:© 2018 The Institution of Engineering and Technology. Received on 18th January 2018; Accepted on 25th February 2018; E-First on 22nd May 2018.
Issue or Number:6
Record Number:CaltechAUTHORS:20180912-154532671
Persistent URL:
Official Citation:L. Majzoobi, V. Shah-Mansouri and F. Lahouti, "Analysis of distributed ADMM algorithm for consensus optimisation over lossy networks," in IET Signal Processing, vol. 12, no. 6, pp. 786-794, 8 2018. doi: 10.1049/iet-spr.2018.0033
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:89598
Deposited By: Tony Diaz
Deposited On:12 Sep 2018 23:27
Last Modified:16 Nov 2021 00:36

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