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• W2989775024 startingPage "69" @default.
• W2989775024 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." @default.
• W2989775024 created "2019-12-05" @default.
• W2989775024 creator A5006424433 @default.
• W2989775024 creator A5071339746 @default.
• W2989775024 date "2020-01-01" @default.
• W2989775024 modified "2023-09-23" @default.
• W2989775024 title "An Efficient Multi-Objective Model for Data Replication in Cloud Computing Environment" @default.
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• W2989775024 doi "https://doi.org/10.4018/ijeis.2020010104" @default.
• W2989775024 hasPublicationYear "2020" @default.
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