On the Structural Perspective of Computational Effectiveness for Quantized Consensus in Layered UAV Networks
Distributed computing tasks in small unmanned aerial vehicle (UAV) networks require effective data transmission schemes because of limited communication channels and transmission power. In this paper, we use decentralized consensus as a canonical distributed computing task to study the effectiveness of the data transmission in digitized (quantized) channels for UAV networks. We show that layered structures are more effective than equivalent egalitarian structures in terms of the data transmission load required to reach consensus. In particular, we establish explicit relationships between simple structural characteristics and the performance of quantized consensus (e.g., consensus condition, consensus value, and transmission load to reach consensus) for broad classes of layered structures. We also provide analytical results on asymptotic and transient performance when additional local memories are used to further reduce the data transmission load to reach consensus.
Y. Wan et al., "On the Structural Perspective of Computational Effectiveness for Quantized Consensus in Layered UAV Networks," IEEE Transactions on Control of Network Systems, vol. 6, no. 1, pp. 276 - 288, Institute of Electrical and Electronics Engineers (IEEE), Mar 2019.
The definitive version is available at https://doi.org/10.1109/TCNS.2018.2813926
Intelligent Systems Center
Second Research Center/Lab
Center for High Performance Computing Research
Keywords and Phrases
Antennas; Control system analysis; Control systems; Data transfer; Distributed computer systems; Job analysis; Network layers; Quantization (signal); Sensors; Unmanned aerial vehicles (UAV); Vehicle transmissions; Consensus; Data-communication; Layered networks; Network topology; Quantization; Task analysis; Data communication systems; Data communication; Unmanned Aerial Vehicle Networks
International Standard Serial Number (ISSN)
Article - Journal
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Mar 2019
This work was supported by the National Science Foundation under Grant CAREER-1714519 and Grant CRI-1730675. Recommended by Associate Editor Y. Hong.