TAILIEUCHUNG - Báo cáo sinh học: " Research Article Linear High-Order Distributed Average Consensus Algorithm in Wireless Sensor Networks Gang Xiong and Shalinee Kishore"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Research Article Linear High-Order Distributed Average Consensus Algorithm in Wireless Sensor Networks Gang Xiong and Shalinee Kishore | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 373604 6 pages doi 2010 373604 Research Article Linear High-Order Distributed Average Consensus Algorithm in Wireless Sensor Networks Gang Xiong and Shalinee Kishore Department of Electrical and Computer Engineering Lehigh University Bethlehem PA 18015 USA Correspondence should be addressed to Shalinee Kishore skishore@ Received 23 November 2009 Revised 17 March 2010 Accepted 27 May 2010 Academic Editor Husheng Li Copyright 2010 G. Xiong and S. Kishore. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. This paper presents a linear high-order distributed average consensus DAC algorithm for wireless sensor networks. The average consensus property and the convergence rate of the high-order DAC algorithm are analyzed. In particular the convergence rate is determined by the spectral radius of a network topology-dependent matrix. Numerical results indicate that this simple linear high-order DAC algorithm can accelerate the convergence without additional communication overhead and reconfiguration of network topology. 1. Introduction The distributed average consensus DAC algorithm aims to provide distributed nodes in a network agreement on a common measurement known at any one node as the local state information. As such it has many relevant applications in wireless sensor networks 1 2 for example movingobject acquisition and tracking habitat monitoring reconnaissance and surveillance. In the DAC approach average consensus can be sufficiently reached within a connected network by averaging pair-wise local state information at network nodes. In 1 Olfati-Saber et al. established a theoretical framework for the analysis of consensus-based algorithms. In this paper we study a simple approach to .

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