A microservices persistence technique for cloud-based online social data analysis

ORCID Identifiers

0000-0001-6168-2664

Document Type

Article

Source of Publication

Cluster Computing

Publication Date

1-1-2021

Abstract

Social data analysis has become a vital tool for businesses and organisations for mining data from social media and analysing for diverse purposes such as customer opinion mining, pattern recognition and predictive analytics. However, the high level of volatility for social data means application updates due to analytical results requires spontaneous integration. In addition, while cloud computing has been hugely utilised to address computational overhead issues due to the volume of social data, results obtained still fall short of expected levels. Hence, a persistence mechanism for rapid deployment and integration of software updates for the analytical process is proposed. The persistence mechanism constitutes a significant component within a novel methodology which also leverages cloud computing, microservices and orchestration for online social data analysis, one which fully maximises cloud capabilities and fosters optimisation of cloud computing resources. The proposed methodology provides means of delivering real-time, persistent social data analytics as a cloud service, thereby facilitating spontaneous integration of solutions to maximise expectations from targeted social media audience.

ISSN

1386-7857

Publisher

Springer Science and Business Media LLC

Disciplines

Computer Sciences

Keywords

Cloud computing, Cloud orchestration, Persistent microservices, Persistent social data, Social data analysis, Social networks

Scopus ID

85103371314

Indexed in Scopus

yes

Open Access

no

Link to Full Text

Share

COinS