Convergence Rate Estimate of Distributed Localization Algorithms in Wireless Sensor Networks | Zendy

Shujuan Pang | Zendy

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Convergence Rate Estimate of Distributed Localization Algorithms in Wireless Sensor Networks

Author(s) -

Shujuan Pang

Publication year - 2015

Publication title -

international journal of distributed sensor networks

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.324

H-Index - 53

eISSN - 1550-1477

pISSN - 1550-1329

DOI - 10.1155/2015/523285

Subject(s) - rate of convergence , convergence (economics) , computer science , wireless sensor network , algorithm , mathematical optimization , wireless , exponential function , distributed algorithm , mathematics , distributed computing , telecommunications , computer network , channel (broadcasting) , mathematical analysis , economics , economic growth

Localization is one of the most important problems in wireless sensor networks. In this paper, we investigate the convergence rate estimate problem of a distributed localization algorithm which approximately formulates the localization problem as the convex feasibility problem including the consistent case and the inconsistent case. Although existing works established optimal consensus convergence analysis for this algorithm, they did not provide the convergence rate estimate. In this paper, we mainly show that for the consistent case the convergence rate of the optimal consensus will be exponential under some basic conditions, while for the inconsistent case we provide a necessary condition for the optimal consensus and a convergence rate estimate inequality. Furthermore, numerical examples are also provided to validate the established convergence and convergence rate results.

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