Dynamic replication based on a data classification model in cloud computing

Abstract

Cloud Computing provides on demand resources for customers and enterprises to outsource their online activities efficiently and less expensively. However, the cloud environment is heterogeneous and very dynamic, storage node failures and increasing demands on data can lead to data unavailability situations leading to a decrease in quality of service. Cloud service providers face the challenge of ensuring maximum data availability and reliability. Replication of data to different nodes in the cloud has become the most common solution for achieving good performance in terms of load balancing, response time and availability. In this article, we propose a new dynamic replication strategy based on a data classification model that would adapt the replication process according to user behavior towards data. This strategy dynamically and adaptively creates the replicas necessary in order to obtain the desired performance such as, reduced response time and improved system availability while ensuring the quality of service. The solution also attempts to meet customer requirements by respecting the SLA contract. The CloudSim simulator was used to evaluate the proposed strategy and compare it to other strategies. The results obtained showed an improvement in the criteria studied in a satisfactory manner.