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.
Original language | English |
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Pages (from-to) | 609-627 |
Number of pages | 19 |
Journal | Computational Optimization and Applications |
Volume | 52 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Jul 2012 |
Externally published | Yes |
Keywords
- Individual trace
- Semidefinite programming relaxation
- Sensor network localization
- Sum of squares relaxation
ASJC Scopus subject areas
- Applied Mathematics
- Computational Mathematics
- Control and Optimization