We advocate a novel concept of dependable intelligent edge systems (DIES) i.e., the edge systems ensuring a high degree of dependability (e.g., security, safety, and robustness) and autonomy because of their applications in critical domains. Building DIES entail a paradigm shift in architectures for acquiring, storing, and processing potentially large amounts of complex data: data management is placed at the edge between the data sources and local processing entities, with loose coupling to storage and processing services located in the cloud. As such, the literal definition of edge and intelligence is adopted, i.e., the ability to acquire and apply knowledge and skills is shifted towards the edge of the network, outside the cloud infrastructure. This paradigm shift offers flexibility, auto configuration, and auto diagnosis, but also introduces novel challenges.

Big data from the cloud to the edge: The aggregate computing solution

Damiani F.
;
2019-01-01

Abstract

We advocate a novel concept of dependable intelligent edge systems (DIES) i.e., the edge systems ensuring a high degree of dependability (e.g., security, safety, and robustness) and autonomy because of their applications in critical domains. Building DIES entail a paradigm shift in architectures for acquiring, storing, and processing potentially large amounts of complex data: data management is placed at the edge between the data sources and local processing entities, with loose coupling to storage and processing services located in the cloud. As such, the literal definition of edge and intelligence is adopted, i.e., the ability to acquire and apply knowledge and skills is shifted towards the edge of the network, outside the cloud infrastructure. This paradigm shift offers flexibility, auto configuration, and auto diagnosis, but also introduces novel challenges.
2019
13th European Conference on Software Architecture, ECSA 2019
FIAP, fra
2019
ACM International Conference Proceeding Series
Association for Computing Machinery
2
177
182
9781450371421
https://dl.acm.org/doi/10.1145/3344948.3344988
Adaptation; Dependability; Formal methods
Ali S.; Damiani F.; Dustdar S.; Sanseverino M.; Viroli M.; Weyns D.
File in questo prodotto:
File Dimensione Formato  
SACBD-2019-Ali-et-al.pdf

Accesso riservato

Descrizione: Articolo principale (workshop)
Tipo di file: PDF EDITORIALE
Dimensione 3 MB
Formato Adobe PDF
3 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
main.pdf

Accesso aperto

Descrizione: Articolo principale (workshop)
Tipo di file: POSTPRINT (VERSIONE FINALE DELL’AUTORE)
Dimensione 900.3 kB
Formato Adobe PDF
900.3 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1736172
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact