The Big Data community has started noticing that there is the need to complete Big Data platforms with assurance techniques proving the correct behavior of Big Data analytics and management. In this paper, we propose a Big Data assurance solution based on Service-Level Agreements (SLAs), focusing on a platform providing Model-based Big Data Analytics-As-A-Service (MBDAaaS).

Big data assurance evaluation: An sla-based approach / C.A. Ardagna, E. Damiani, M. Krotsiani, C. Kloukinas, G. Spanoudakis - In: 2018 IEEE International Conference on Services Computing (SCC)[s.l] : IEEE, 2018. - ISBN 9781538672501. - pp. 299-303 (( convegno International Conference on Services Computing tenutosi a San Francisco nel 2018 [10.1109/SCC.2018.00053].

Big data assurance evaluation: An sla-based approach

C.A. Ardagna;E. Damiani;
2018

Abstract

The Big Data community has started noticing that there is the need to complete Big Data platforms with assurance techniques proving the correct behavior of Big Data analytics and management. In this paper, we propose a Big Data assurance solution based on Service-Level Agreements (SLAs), focusing on a platform providing Model-based Big Data Analytics-As-A-Service (MBDAaaS).
Assurance, Big Data, SLA; Computer Science Applications1707 Computer Vision and Pattern Recognition; Computer Networks and Communications; Hardware and Architecture; Information Systems and Management
Settore INF/01 - Informatica
   TrustwOrthy model-awaRE Analytics Data platfORm
   TOREADOR
   EUROPEAN COMMISSION
   H2020
   688797
2018
IEEE
IEEE Computer Society
Book Part (author)
File in questo prodotto:
File Dimensione Formato  
Big Data Assurance Evaluation An SLA-Based Approach.pdf

accesso riservato

Tipologia: Post-print, accepted manuscript ecc. (versione accettata dall'editore)
Dimensione 135.11 kB
Formato Adobe PDF
135.11 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

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/2434/595989
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 0
social impact