Integration Model between Heterogeneous Data Services in a Cloud

Abstract

With the growth of cloud services, many companies have begun to persist and make their data available through services such as Data as a Service (DaaS) and Database as a Service (DBaaS). The DaaS model provides on-demand data through an Application Programming Inter- face (API), while DBaaS model provides on-demand database management systems. Different data sources require efforts to integrate data from different models. These model types include unstructured, semi-structured, and structured data. Heterogeneity from DaaS and DBaaS makes it challenging to integrate data from different services. In response to this problem, we developed the Data Join (DJ) method to integrate heterogeneous DaaS and DBaaS sources. DJ was described through canonical models and incorporated into a middleware as a proof-of-concept. A test case and three experiments were performed to validate our DJ method: the first experiment tackles data from DaaS and DBaaS in isolation; the second experiment associates data from different DaaS and DBaaS through one join clause; and the third experiment integrates data from three sources (one DaaS and two DBaaS) based on different data type (relational, NoSQL, and NewSQL) through two join clauses. Our experiments evaluated the viability, functionality, integration, and performance of the DJ method. Results demonstrate that DJ method outperforms most of the related work on selecting and integrating data in a cloud environment.

Incident Management for Explainable and Automated Root Cause Analysis in Cloud Data Centers    

“…One of the important elements of the analytics is RCA on all acquired data for an anomaly detection, problem identification and self-remediation, risk management, intrusion detection, etc. (see [Mirgorodskiy et al, 2006, Mi et al, 2012, Agarwal and Agrawal, 2014, Kostroš et al, 2014, Wang et al, 2015, Sauvanaud et al, 2016, Tak et al, 2016, Solé et al, 2017, Neuvirth et al, 2015, Josefsson, 2017, Harutyunyan et al, 2018b, Harutyunyan et al, 2020b, Chen et al, 2020, Das et al, 2020, Ferreira et al, 2020, Salaün et al, 2020, Bonandrini et al, 2020, Marcia et al, 2021, Jedrzej et al, 2019, Bilal et al, 2021, Vieira et al, 2021, Mejía et al, 2021, Ibrahim Kure and Islam, 2019 with references therein).…”