An Efficient Multi-Objective Model for Data Replication in Cloud Computing Environment

Abstract

The main aim of the proposed methodology is to design a multi-objective function for replica management system using oppositional gravitational search algorithm (OGSA), in which we analyze the various factors influencing replication decisions such as mean service time, mean file availability, energy consumption, load variance, and mean access latency. The OGSA algorithm is hybridization of oppositional-based learning (OBL) and gravitational search algorithm (GSA), which is change existing solution, and to adopt a new good solution based on objective function. Here, firstly we create a set of files and data node to generate a population by assigning the file to data node randomly and evaluate the fitness which is minimizing the objective function. Secondly, we regenerate the population to produce optimal or suboptimal population using OGSA. The experimental results show that the performance of the proposed methods is better than the other methods of data replication problem.

Performance Enhancement of Cloud Datacenters Through Replicated Database Server

“…However, none of these articles focuses the energy efficiency or on minimization of the energy consumption or the replication strategies by the data centres. In this paper, we present a data replication technique for cloud computing data centres which minimizes the energy consumption and increases the energy efficiency, optimizes the network bandwidth and decreases the communication delay among the geographically distributed data centres and also inside each datacenter (Sasikumar et al (2020)). Specifically, our contributions in this can be summarized as follows.…”