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Effective Data Transfers through Parallelism in Cloud Networks


  • Department of Information Technology, SRM University, Chennai - 603203, Tamil Nadu, India


Objectives: We aim at analyzing a method that enhances throughput for huge heterogeneous file transfers in the inter cloud and intra cloud for data transfers. Method: The proposed work identifies the files to be transferred in the cloud, splits the data packet into chunks and pushes them to the cache storage from where they are transferred onto the destination cloud. This method helps in enhancing the throughput of the data being transferred and simulations are observed. Findings: Generally, the previous methods focused on considering the file for being large or small and then predicting to use pipeline or parallelism. In this work, we transfer the file irrespective of the size by splitting it into a reasonable chunk of data for effective utitilization of the available bandwidth. Application/Improvements: Consideration with large and small files and then splitting them takes more time with chances of data being lost or not utilized. Hence, our work features more on assuring that the data is being sent to the cloud with no data loss.


Big Data Transfer, Heterogeneous File, Inter-Cloud Transfer, Parallelism, Throughput.

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