IoT Data Replication and Consistency Management in Fog computing - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of Grid Computing Année : 2021

IoT Data Replication and Consistency Management in Fog computing

Résumé

Fog Computing has emerged as a virtual platform extending Cloud services down to the network edge especially (and not exclusively) to host IoT applications. Data replication strategies have been designed to investigate the best storage location of data copies in geo-distributed storage systems in order to reduce its access time for different consumer services spread over the infrastructure. Unfortunately, due to the geographical distance between Fog nodes, misplacing data in such an infrastructure may generate high latencies when accessing or synchronizing replicas, thus degrading the Quality of Service (QoS). In this paper, we present two strategies to manage IoT data replication and consistency in Fog infrastructures. Our strategies choose for each datum, the right replica number and their location in order to reduce data access latency and replicas synchronization cost. This is done while respecting the required consistency level. Also, we propose an evaluation platform based on the simulator iFogSim to enable users to implement and test their own strategies for IoT data replication and consistency management. Our experiments show that when using our strategies, the service latency can be reduced by 30% in case of small Fog infrastructures and by 13% in case of large scale Fog infrastructures compared to iFogStor, a state-of-the-art strategy that does not use replication.
Fichier principal
Vignette du fichier
IoT_Data_Naas_Rev1.pdf (836.19 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03349814 , version 1 (20-09-2021)

Identifiants

Citer

Mohammed Islam Naas, Laurent Lemarchand, Philippe Raipin, Jalil Boukhobza. IoT Data Replication and Consistency Management in Fog computing. Journal of Grid Computing, 2021, 19 (3), pp.33. ⟨10.1007/s10723-021-09571-1⟩. ⟨hal-03349814⟩
169 Consultations
245 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More