Decentralized consensus in distributed networks. Issue 6 (2nd November 2018)

• Record Type: Journal Article
• Authors: Zhao, Liang; Song, WenZhan
• Is Part Of: International journal of parallel, emergent and distributed systems. Volume 33:Issue 6(2018)
• Page Start: 550
• Page End: 569
• Publication Date: 2018-11-02
• Subjects: Big data -- decentralised computing -- in-network processing -- seismic tomography -- sensor network; Parallel computers -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Computer algorithms -- Periodicals; 004.35
• DOI: 10.1080/17445760.2016.1233552
• Languages: English
• ISSNs: 1744-5760

Abstract

Abstract: We consider the decentralised consensus optimization problem in this paper. A fast decentralised gradient-based algorithm is proposed for a general class of problems with convex and differentiable objective functions. The developed method guarantees that all the nodes in the network would reach consensus on the global variable eventually. Based on the proposed decentralised algorithm, a broadcast-based protocol is designed, which is capable of providing solution for real-time in situ seismic imaging. Extensive numerical experiments on both synthetic and real sensor network seismic data sets validate the superior efficiency of the proposed algorithm over the other benchmarks. Graphical Abstract: It is the architecture of the seismic tomography in sensor networks.