A Brief Survey on Replica Consistency in Cloud Environments

TL;DR

This survey reviews various methods addressing data consistency challenges in geographically-distributed cloud storage systems, categorizing them into fixed, configurable, and monitoring approaches to ensure reliable data replication.

Contribution

It provides a comprehensive categorization and analysis of recent consistency techniques in cloud data storage, highlighting their differences and applications.

Findings

Most methods focus on balancing consistency and performance.

Configurable methods offer flexible consistency levels.

Monitoring approaches help detect and maintain consistency.

Abstract

Cloud computing is a general term that involves delivering hosted services over the Internet. With the accelerated growth of the volume of data used by applications, many organizations have moved their data into cloud servers to provide scalable, reliable and highly available services. A particularly challenging issue that arises in the context of cloud storage systems with geographically-distributed data replication is how to reach a consistent state for all replicas. This survey reviews major aspects related to consistency issues in cloud data storage systems, categorizing recently proposed methods into three categories: (1) fixed consistency methods, (2) configurable consistency methods and (3) consistency monitoring methods.