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Accomplishing Minimum Data Sets Transfer Cost in the Cloud through Ant Colony Optimization

Thahassin.C, A.Geetha, Raseek.C

The booming volume of data generated by contemporary business users and consumers have created enormous data storage and management challenges. Cloud computing provides a way to enable massive amounts of data to work together as data-intensive services. Many users are moving their data to online storage clouds, where data are stored based on the pay-as-you-go model. There are many cost-effective approaches have been developed for achieving minimum cost benchmark. However, it may not be sufficient, if large-scale applications have to run in a more distributed manner. In this paper, for incorporating data transfer cost into minimum cost benchmark, an effective Ant Colony Optimization (ACO) algorithm has been proposed. ACO reduces the delay in accessing & transferring the data sets which paves the way to achieve a minimum cost benchmark.