Distributed Change Detection in Streaming Graph Signals - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

Distributed Change Detection in Streaming Graph Signals

André Ferrari
Cédric Richard
Louis Verduci
  • Fonction : Auteur

Résumé

Detecting abrupt changes in streaming graph signals is relevant in a variety of applications ranging from energy and water supplies, to environmental monitoring. In this paper, we address this problem when anomalies activate localized groups of nodes in a network. We introduce an online change-point detection algorithm, which is fully distributed across nodes to monitor large-scale dynamic networks. We analyze the detection statistics for controlling the probability of a global type 1 error. Finally we illustrate the detection and localization performance with simulated data. This work was funded by the French government labelled PIA program under its IDEX UCAJEDI project (ANR-15-IDEX-0001).
Fichier principal
Vignette du fichier
ferrari2019distributed.pdf (730.8 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03634121 , version 1 (07-04-2022)

Identifiants

Citer

André Ferrari, Cédric Richard, Louis Verduci. Distributed Change Detection in Streaming Graph Signals. 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Dec 2019, Le gosier, France. pp.166-170, ⟨10.1109/CAMSAP45676.2019.9022658⟩. ⟨hal-03634121⟩
11 Consultations
10 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More