PADL: A Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments

Josu Díaz-De-Arcaya; Raúl Miñón; Ana I. Torre-Bastida; Javier Del Ser; Aitor Almeida

doi:10.23919/SpliTech49282.2020.9243735

PADL: A Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments

AI

University of Deusto

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

In this paper we introduce PADL, a language for modeling and deploying data-based analytical pipelines. The novelty of this language relies on its independence from both the infrastructure and the technologies used on it. Specifically, this descriptive language aims at embracing all the particularities and constraints of high-demanding deployment models, such as critical restrictions regarding latency, privacy and performance, by providing fully-compliant schemas for implementing data analytical workloads. The adoption of PADL provides means for the operationalization of these pipelines in a reproducible and resilient fashion. In addition, PADL is able to fully utilize the benefits of Edge and Fog computing layers. The feasibility of the language has been validated with an analytical pipeline deployed over an Edge computing environment to solve an Industry 4.0 use case. The promising results obtained therefrom pave the way towards the widespread adoption of our proposed language when deploying data analytical pipelines over real application scenarios.

Original language	English
Title of host publication	2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020
Editors	Petar Solic, Sandro Nizetic, Joel J. P. C. Rodrigues, Joel J. P.C. Rodrigues, Diego Lopez-de-Ipina Gonzalez-de-Artaza, Toni Perkovic, Luca Catarinucci, Luigi Patrono
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9789532901054
DOIs	https://doi.org/10.23919/SpliTech49282.2020.9243735
Publication status	Published - 23 Sept 2020
Event	5th International Conference on Smart and Sustainable Technologies, SpliTech 2020 - Virtual, Split, Croatia Duration: 23 Sept 2020 → 26 Sept 2020

Publication series

Name	2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020

Conference

Conference	5th International Conference on Smart and Sustainable Technologies, SpliTech 2020
Country/Territory	Croatia
City	Virtual, Split
Period	23/09/20 → 26/09/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

AI domain specific language
analytical pipelines
edge computing
machine learning life cycle

Access to Document

10.23919/SpliTech49282.2020.9243735

Cite this

Díaz-De-Arcaya, J., Miñón, R., Torre-Bastida, A. I., Del Ser, J., & Almeida, A. (2020). PADL: A Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments. In P. Solic, S. Nizetic, J. J. P. C. Rodrigues, J. J. P. C. Rodrigues, D. Lopez-de-Ipina Gonzalez-de-Artaza, T. Perkovic, L. Catarinucci, & L. Patrono (Eds.), 2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020 Article 9243735 (2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/SpliTech49282.2020.9243735

Díaz-De-Arcaya, Josu ; Miñón, Raúl ; Torre-Bastida, Ana I. et al. / PADL : A Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments. 2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020. editor / Petar Solic ; Sandro Nizetic ; Joel J. P. C. Rodrigues ; Joel J. P.C. Rodrigues ; Diego Lopez-de-Ipina Gonzalez-de-Artaza ; Toni Perkovic ; Luca Catarinucci ; Luigi Patrono. Institute of Electrical and Electronics Engineers Inc., 2020. (2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020).

@inproceedings{ec56c3fcaed34618b171e8522926bdaa,

title = "PADL: A Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments",

abstract = "In this paper we introduce PADL, a language for modeling and deploying data-based analytical pipelines. The novelty of this language relies on its independence from both the infrastructure and the technologies used on it. Specifically, this descriptive language aims at embracing all the particularities and constraints of high-demanding deployment models, such as critical restrictions regarding latency, privacy and performance, by providing fully-compliant schemas for implementing data analytical workloads. The adoption of PADL provides means for the operationalization of these pipelines in a reproducible and resilient fashion. In addition, PADL is able to fully utilize the benefits of Edge and Fog computing layers. The feasibility of the language has been validated with an analytical pipeline deployed over an Edge computing environment to solve an Industry 4.0 use case. The promising results obtained therefrom pave the way towards the widespread adoption of our proposed language when deploying data analytical pipelines over real application scenarios.",

keywords = "AI domain specific language, analytical pipelines, edge computing, machine learning life cycle",

author = "Josu D{\'i}az-De-Arcaya and Ra{\'u}l Mi{\~n}{\'o}n and Torre-Bastida, \{Ana I.\} and \{Del Ser\}, Javier and Aitor Almeida",

note = "Publisher Copyright: {\textcopyright} 2020 University of Split, FESB.; 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020 ; Conference date: 23-09-2020 Through 26-09-2020",

year = "2020",

month = sep,

day = "23",

doi = "10.23919/SpliTech49282.2020.9243735",

language = "English",

series = "2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Petar Solic and Sandro Nizetic and Rodrigues, \{Joel J. P. C.\} and Rodrigues, \{Joel J. P.C.\} and \{Lopez-de-Ipina Gonzalez-de-Artaza\}, Diego and Toni Perkovic and Luca Catarinucci and Luigi Patrono",

booktitle = "2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020",

address = "United States",

}

Díaz-De-Arcaya, J , Miñón, R , Torre-Bastida, AI , Del Ser, J & Almeida, A 2020, PADL: A Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments. in P Solic, S Nizetic, JJPC Rodrigues, JJPC Rodrigues, D Lopez-de-Ipina Gonzalez-de-Artaza, T Perkovic, L Catarinucci & L Patrono (eds), 2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020., 9243735, 2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020, Institute of Electrical and Electronics Engineers Inc., 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020, Virtual, Split, Croatia, 23/09/20. https://doi.org/10.23919/SpliTech49282.2020.9243735

PADL: A Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments. / Díaz-De-Arcaya, Josu ; Miñón, Raúl ; Torre-Bastida, Ana I. et al.
2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020. ed. / Petar Solic; Sandro Nizetic; Joel J. P. C. Rodrigues; Joel J. P.C. Rodrigues; Diego Lopez-de-Ipina Gonzalez-de-Artaza; Toni Perkovic; Luca Catarinucci; Luigi Patrono. Institute of Electrical and Electronics Engineers Inc., 2020. 9243735 (2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - PADL

T2 - 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020

AU - Díaz-De-Arcaya, Josu

AU - Miñón, Raúl

AU - Torre-Bastida, Ana I.

AU - Del Ser, Javier

AU - Almeida, Aitor

PY - 2020/9/23

Y1 - 2020/9/23

N2 - In this paper we introduce PADL, a language for modeling and deploying data-based analytical pipelines. The novelty of this language relies on its independence from both the infrastructure and the technologies used on it. Specifically, this descriptive language aims at embracing all the particularities and constraints of high-demanding deployment models, such as critical restrictions regarding latency, privacy and performance, by providing fully-compliant schemas for implementing data analytical workloads. The adoption of PADL provides means for the operationalization of these pipelines in a reproducible and resilient fashion. In addition, PADL is able to fully utilize the benefits of Edge and Fog computing layers. The feasibility of the language has been validated with an analytical pipeline deployed over an Edge computing environment to solve an Industry 4.0 use case. The promising results obtained therefrom pave the way towards the widespread adoption of our proposed language when deploying data analytical pipelines over real application scenarios.

AB - In this paper we introduce PADL, a language for modeling and deploying data-based analytical pipelines. The novelty of this language relies on its independence from both the infrastructure and the technologies used on it. Specifically, this descriptive language aims at embracing all the particularities and constraints of high-demanding deployment models, such as critical restrictions regarding latency, privacy and performance, by providing fully-compliant schemas for implementing data analytical workloads. The adoption of PADL provides means for the operationalization of these pipelines in a reproducible and resilient fashion. In addition, PADL is able to fully utilize the benefits of Edge and Fog computing layers. The feasibility of the language has been validated with an analytical pipeline deployed over an Edge computing environment to solve an Industry 4.0 use case. The promising results obtained therefrom pave the way towards the widespread adoption of our proposed language when deploying data analytical pipelines over real application scenarios.

KW - AI domain specific language

KW - analytical pipelines

KW - edge computing

KW - machine learning life cycle

UR - https://www.scopus.com/pages/publications/85096562659

U2 - 10.23919/SpliTech49282.2020.9243735

DO - 10.23919/SpliTech49282.2020.9243735

M3 - Conference contribution

AN - SCOPUS:85096562659

T3 - 2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020

BT - 2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020

A2 - Solic, Petar

A2 - Nizetic, Sandro

A2 - Rodrigues, Joel J. P. C.

A2 - Rodrigues, Joel J. P.C.

A2 - Lopez-de-Ipina Gonzalez-de-Artaza, Diego

A2 - Perkovic, Toni

A2 - Catarinucci, Luca

A2 - Patrono, Luigi

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 23 September 2020 through 26 September 2020

ER -

Díaz-De-Arcaya J , Miñón R , Torre-Bastida AI , Del Ser J, Almeida A. PADL: A Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments. In Solic P, Nizetic S, Rodrigues JJPC, Rodrigues JJPC, Lopez-de-Ipina Gonzalez-de-Artaza D, Perkovic T, Catarinucci L, Patrono L, editors, 2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9243735. (2020 5th International Conference on Smart and Sustainable Technologies, SpliTech 2020). doi: 10.23919/SpliTech49282.2020.9243735

PADL: A Language for the Operationalization of Distributed Analytical Pipelines over Edge/Fog Computing Environments

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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