This article introduces a novel hybrid workflow abstraction that injects topology awareness directly into the definition of a distributed workflow model. In particular, the article briefly discusses the advantages brought by this approach to the design and orchestration of large-scale data-oriented workflows, the current level of support from state-of-the-art workflow systems, and some future research directions.

Workflow Models for Heterogeneous Distributed Systems

Iacopo Colonnelli
First
2023-01-01

Abstract

This article introduces a novel hybrid workflow abstraction that injects topology awareness directly into the definition of a distributed workflow model. In particular, the article briefly discusses the advantages brought by this approach to the design and orchestration of large-scale data-oriented workflows, the current level of support from state-of-the-art workflow systems, and some future research directions.
2023
Inglese
su invito
1 - Conferenza
2nd Italian Conference on Big Data and Data Science 2023 (ITADATA 2023)
Napoli, Italy
September 11-13, 2023
Proceedings of the 2nd Italian Conference on Big Data and Data Science (ITADATA 2023)
Comitato scientifico
CEUR-WS
Aachen
GERMANIA
3606
1
4
4
https://ceur-ws.org/Vol-3606/invited77.pdf
Scientific Workflows, HPC, Cloud Computing, Distributed Computing, Hybrid Workflows
no
   HPC BIG DATA ARTIFICIAL INTELLIGENCE CROSS STACK PLATFORM TOWARDS EXASCALE
   ACROSS
   European Commission
   Horizon 2020 Framework Programme
   955648

   EUROPEAN PILOT FOR EXASCALE
   EUPEX
   European Commission
   Horizon 2020 Framework Programme
   101033975
1 – prodotto con file in versione Open Access (allegherò il file al passo 6 - Carica)
1
info:eu-repo/semantics/conferenceObject
04-CONTRIBUTO IN ATTI DI CONVEGNO::04A-Conference paper in volume
Iacopo Colonnelli
273
open
File in questo prodotto:
File Dimensione Formato  
invited77.pdf

Accesso aperto

Descrizione: PDF Editoriale
Tipo di file: PDF EDITORIALE
Dimensione 780.45 kB
Formato Adobe PDF
780.45 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/2318/1955030
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact