Latency-Aware Placement of Data Stream Analytics on Edge Computing - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2018

Latency-Aware Placement of Data Stream Analytics on Edge Computing

Résumé

The interest in processing data events under stringent time constraints as they arrive has led to the emergence of architecture and engines for data stream processing. Edge computing, initially designed to minimize the latency of content delivered to mobile devices, can be used for executing certain stream processing operations. Moving operators from cloud to edge, however, is challenging as operator-placement decisions must consider the application requirements and the network capabilities. In this work, we introduce strategies to create placement configurations for data stream processing applications whose operator topologies follow series parallel graphs. We consider the operator characteristics and requirements to improve the response time of such applications. Results show that our strategies can improve the response time in up to 50% for application graphs comprising multiple forks and joins while transferring less data and better using the resources.
Fichier principal
Vignette du fichier
icsoc_2018.pdf (575.78 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01875936 , version 1 (18-09-2018)

Identifiants

  • HAL Id : hal-01875936 , version 1

Citer

Alexandre da Silva Veith, Marcos Dias de Assuncao, Laurent Lefèvre. Latency-Aware Placement of Data Stream Analytics on Edge Computing. Service-Oriented Computing, Nov 2018, Hangzhou, Zhejiang, China. pp.215-229. ⟨hal-01875936⟩
226 Consultations
889 Téléchargements

Partager

More