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Artifact: Implementation of an Adaptive Flow Management Framework for IoT Spaces

  • CNRS UMR 5157 SAMOVAR
  • Ericsson Ai Research

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collectionContribution à une conférenceRevue par des pairs

Résumé

This paper presents the implementation and guideline of PlanIoT, an adaptive flow management framework for IoT-enhanced spaces. Such spaces are composed of applications deployed at the Edge with varying QoS requirements in terms of response time, timely delivery, throughput, etc. Configuring the Edge infrastructure requires tuning multiple parameters for optimal QoS satisfaction of applications. This is a complex task especially when the system has to be re-adapted (e.g., emergency situations). The PlanIoT framework manages application data flows in an adaptive manner. This is achieved via the following core software components: (i) a queueing network composer; (ii) an automated planning modeler; and (iii) an AI planner. This artifact presents implementation details of these components as well as guidelines for using the PlanIoT framework.

langue originaleAnglais
titreProceedings - 2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2023
EditeurIEEE Computer Society
Pages188-194
Nombre de pages7
ISBN (Electronique)9798350311921
Les DOIs
étatPublié - 1 janv. 2023
Evénement18th IEEE/ACM Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2023 - Melbourne, Australie
Durée: 15 mai 202316 mai 2023

Série de publications

NomICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems
Volume2023-May
ISSN (imprimé)2157-2305
ISSN (Electronique)2156-7891

Une conférence

Une conférence18th IEEE/ACM Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2023
Pays/TerritoireAustralie
La villeMelbourne
période15/05/2316/05/23

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