TY - GEN
T1 - Distributed Quantized Weight-Balancing and Average Consensus over Digraphs
AU - Lee, Chang Shen
AU - Michelusi, Nicolo
AU - Scutari, Gesualdo
N1 - Funding Information:
Lee and Michelusi are with the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA. Scutari is with the School of Industrial Engineering, Purdue University, West Lafayette, IN, USA. Emails: <lee2495,michelus,gscutari>@purdue.edu. This work was supported by USA NSF under Grants CIF 1632599 and CIF 1719205; and in part by the ONR under Grant N00014-16-1-2244 and the ARO Grant W911NF-18-1-0238.
Funding Information:
This work was supported by USA NSF under Grants CIF 1632599 and CIF 1719205; and in part by the ONR under Grant N00014-16-1-2244 and the ARO Grant W911NF-18-1-0238.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - This paper studies distributed quantized weight-balancing and average consensus over fixed digraphs. A digraph with non-negative weights associated to its edges is weight-balanced if, for each node, the sum of the weights of its outgoing edges is equal to that of its incoming edges. We propose and analyze the first distributed algorithm that solves the weight-balancing problem using only quantized (one-bit) information among nodes and simplex communications (compliant to the directed nature of the graph edges). Asymptotic convergence of the scheme is proved and a convergence rate analysis is provided. Building on this result, a novel distributed algorithm is proposed that solves the average consensus problem over digraphs, using, at each iteration, only two-bit simplex communications between adjacent nodes - one bit for the weight-balancing problem, the other for the average consensus. Convergence to the average of the real (i.e., unquantized) node's initial values is proved, both almost surely and in mean square sense. Finally, numerical results validate our theoretical findings.
AB - This paper studies distributed quantized weight-balancing and average consensus over fixed digraphs. A digraph with non-negative weights associated to its edges is weight-balanced if, for each node, the sum of the weights of its outgoing edges is equal to that of its incoming edges. We propose and analyze the first distributed algorithm that solves the weight-balancing problem using only quantized (one-bit) information among nodes and simplex communications (compliant to the directed nature of the graph edges). Asymptotic convergence of the scheme is proved and a convergence rate analysis is provided. Building on this result, a novel distributed algorithm is proposed that solves the average consensus problem over digraphs, using, at each iteration, only two-bit simplex communications between adjacent nodes - one bit for the weight-balancing problem, the other for the average consensus. Convergence to the average of the real (i.e., unquantized) node's initial values is proved, both almost surely and in mean square sense. Finally, numerical results validate our theoretical findings.
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U2 - 10.1109/CDC.2018.8618973
DO - 10.1109/CDC.2018.8618973
M3 - Conference contribution
AN - SCOPUS:85062175377
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 5857
EP - 5862
BT - 2018 IEEE Conference on Decision and Control, CDC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 57th IEEE Conference on Decision and Control, CDC 2018
Y2 - 17 December 2018 through 19 December 2018
ER -