6533b827fe1ef96bd1286662
RESEARCH PRODUCT
Location-Awareness for Failure Management in Cellular Networks: An Integrated Approach
Raquel BarcoSergio FortesJose Carlos Baena GonzalezZeeshan AsgharEduardo BaenaJavier VillegasMuhammad Asgharsubject
paikkatiedotProcess (engineering)Computer sciencecellular networksmedia_common.quotation_subjectReliability (computer networking)matkaviestinverkot02 engineering and technologylcsh:Chemical technologycomputer.software_genreverkonhallintaBiochemistryCommercializationArticleField (computer science)Analytical Chemistry0203 mechanical engineering0202 electrical engineering electronic engineering information engineeringfailure managementlcsh:TP1-1185Electrical and Electronic EngineeringResilience (network)Instrumentationmedia_commonviatLocation awareness020206 networking & telecommunications020302 automobile design & engineeringlocation-awarenessAtomic and Molecular Physics and OpticsRisk analysis (engineering)positioningKey (cryptography)Cellular networkPsychological resiliencecomputerlangattomat verkotdescription
Recent years have seen the proliferation of different techniques for outdoor and, especially, indoor positioning. Still being a field in development, localization is expected to be fully pervasive in the next few years. Although the development of such techniques is driven by the commercialization of location-based services (e.g., navigation), its application to support cellular management is considered to be a key approach for improving its resilience and performance. When different approaches have been defined for integrating location information into the failure management activities, they commonly ignore the increase in the dimensionality of the data as well as their integration into the complete flow of networks failure management. Taking this into account, the present work proposes a complete integrated approach for location-aware failure management, covering the gathering of network and positioning data, the generation of metrics, the reduction in the dimensionality of such data, and the application of inference mechanisms. The proposed scheme is then evaluated by system-level simulation in ultra-dense scenarios, showing the capabilities of the approach to increase the reliability of the supported diagnosis process as well as reducing its computational cost.
year | journal | country | edition | language |
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2021-02-22 |