test_moissonnage_selune
type: Agent

Detection and localization of link-level network anomalies using end-to-end path monitoring
type: Dataset
contact point: Organization
  fn: CCSD
keyword: anomaly-detection
keyword: anomaly-localization
keyword: monitorage-des-reseaux
keyword: link-level-network-anomalies
keyword: end-to-end-path-monitoring
keyword: detection-des-anomalies
keyword: localisation-des-anomalies
keyword: network-monitoring
keyword: theses
keyword: infoinfo-ohcomputer-science-csother-csoh
keyword: infoeu-reposemanticsdoctoralthesis
keyword: monitorage-des-chemins-de-bout-en-bout
landing page: https://theses.hal.science/tel-00860397
description: The aim of this thesis is to come up with cost-efficient, accurate and fast schemes for link-level network anomaly detection and localization. It has been established that for detecting all potential link-level anomalies, a set of paths that cover all links of the network must be monitored, whereas for localizing all potential link-level anomalies, a set of paths that can distinguish between all links of the network pairwise must be monitored. Either end-node of each path monitored must be equipped with a monitoring device. Most existing link-level anomaly detection and localization schemes are two-step. The first step selects a minimal set of monitor locations that can detect/localize any link-level anomaly. The second step selects a minimal set of monitoring paths between the selected monitor locations such that all links of the network are covered/distinguishable pairwise. However, such stepwise schemes do not consider the interplay between the conflicting optimization objectives of the two steps, which results in suboptimal consumption of the network resources and biased monitoring measurements. One of the objectives of this thesis is to evaluate and reduce this interplay. To this end, one-step anomaly detection and localization schemes that select monitor locations and paths that are to be monitored jointly are proposed. Furthermore, we demonstrate that the already established condition for anomaly localization is sufficient but not necessary. A necessary and sufficient condition that minimizes the localization cost drastically is established. The problems are demonstrated to be NP-Hard. Scalable and near-optimal heuristic algorithms are proposed.
identifier: NNT: 2013REN1S021
issued: 2026-05-09T19:17:59.858001
language: en
modified: 2026-05-09T19:17:59.858005

Detection and localization of link-level network anomalies using end-to-end path monitoring
type: Distribution
access URL: https://theses.hal.science/tel-00860397
format: HTML
issued: 2026-05-09T19:17:59.866342
modified: 2026-05-09T19:17:59.846509