Information diffusion algorithms over WSNs for non-asymptotic confidence region evaluation

Abstract : Getting confidence regions for parameter estimates obtained from data collected by a wireless sensor network (WSN) is very important to assess the performance of the estimator. The sign perturbed sums (SPS) approach has been proposed recently to defined exact confidence regions in a centralized setting even if only few measurements are available. SPS may be distributed to get confidence regions at each node of a WSN. This paper investigates a data dissemination strategy called Tagged and Aggregated Sums (TAS), exploiting the particularities of SPS, to efficiently provide each node with the information necessary to evaluate locally the confidence region. TAS and flooding (FL) algorithms have been investigated through simulations and then implemented on commercial sensor nodes. The impact of collision avoidance mechanisms at the medium access control (MAC) layer is also experimentally assessed. Performance comparisons show that TAS outperforms FL in structured networks. 1
Complete list of metadatas

https://hal-centralesupelec.archives-ouvertes.fr/hal-01576623
Contributor : Michel Kieffer <>
Submitted on : Wednesday, August 23, 2017 - 3:48:44 PM
Last modification on : Thursday, June 20, 2019 - 4:08:07 PM

File

ICC_2017_TAS_AC_GP_V.pdf
Files produced by the author(s)

Identifiers

Citation

Alex Calisti, Davide Dardari, Gianni Pasolini, Michel Kieffer, Francesca Bassi. Information diffusion algorithms over WSNs for non-asymptotic confidence region evaluation. IEEE International Conference on Communications, May 2017, Paris, France. pp.1 - 7, ⟨10.1109/ICC.2017.7997230⟩. ⟨hal-01576623⟩

Share

Metrics

Record views

314

Files downloads

145