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Distributed real-time optimization of average consensus

Yang, Haitao, Wang, Xinheng, Grecos, Christos and Bai, Lin (2013) Distributed real-time optimization of average consensus. In: 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC). IEEE, pp. 102-107. ISBN 9781467324809

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Distributed average consensus (DAC) algorithm is widely used in many applications. It utilizes matrix iteration to find the dominant eigenvector. To minimize the required number of iterations, the algorithm needs to be optimized. However, this optimization needs the knowledge of network topology, which is very hard to obtain for an individual agent in distributed networks. Thus, optimal step length and forgetting factor need to be calculated offline and forwarded to every agent. To solve this problem, we proposed a distributed real-time optimization technique so that each node can estimate these optimal parameters individually. In addition, the method is based on constant first-order DAC itself, so it will not stop the consensus process. The result shows that a numerical error due to quantization would exist in the distributed solution. It will increase as the network becomes larger. Thus, a numerical technique is introduced to mitigate the error. The estimated parameters after mitigation do not obviously decline the performance of higher-order DAC when network size is smaller than a threshold.

Item Type: Book Section
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources
Divisions: School of Computing > Staff Research and Publications
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 05 Mar 2019 12:22
Last Modified: 05 Mar 2019 12:22

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