Comparing SOS and SDP relaxations of sensor network localization

João Gouveia () and Ting Pong ()

Computational Optimization and Applications, 2012, vol. 52, issue 3, 609-627

Abstract: We investigate the relationships between various sum of squares (SOS) and semidefinite programming (SDP) relaxations for the sensor network localization problem. In particular, we show that Biswas and Ye’s SDP relaxation is equivalent to the degree one SOS relaxation of Kim et al. We also show that Nie’s sparse-SOS relaxation is stronger than the edge-based semidefinite programming (ESDP) relaxation, and that the trace test for accuracy, which is very useful for SDP and ESDP relaxations, can be extended to the sparse-SOS relaxation. Copyright Springer Science+Business Media, LLC 2012

Keywords: Sensor network localization; Semidefinite programming relaxation; Sum of squares relaxation; Individual trace (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/s10589-011-9431-1

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