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Effective Data Transfers through Parallelism in Cloud Networks
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.
- Fang X, Veeraraghavan M. A hybrid network architecture for file transfers. IEEE Transactions on Parallel and Distributed Systems. 2009; 20(12):1714–25.
- Hacker TJ, Noble BD, Atley BD. The end-to-end performance effects of parallel tcp sockets on a lossy wide area network. Proc IEEE International Symposium on Parallel and Distributed Processing (IPDPS’02); 2002. p. 434–43.
- Yildirim E, Arslan E, Kim J, Kosar J. Application-level optimization of big data transfers through pipelining, parallelism and concurrency. IEEE Transactions on Cloud Computing. 2016 Jan-Mar; 4(1):63–75.
- Altman E, Barman D, Tuffin B, Vojnovic M. Parallel tcp sockets: Simple model, throughput and validation. Proc IEEE Conference on Computer Communications (INFOCOM’ 06); 2006 Apr. p. 1–12.
- Arslan E, Ross B, Kosar R. Dynamic protocol tuning algorithms for high performance data transfers. Proceedings of the 19th International Conference on Parallel Processing ser Euro-Par’13; 2013. p. 725–36.
- Lining Z, Yunlan W, Jianhua GU, Tianhai Z. Adaptive file transfer and policy study in cloud computing. 2011 IEEE International Conference on Intelligent Computing and Integrated Systems (ICISS); 2013 Jan 1-8.
- Yildrim E, Yin D, Kosar T. Prediction of optimal parallelism level in wide area data transfers. IEEE Transactions on Parallel and Distributed Systems. 2011; 22(12):1–14.
- Yildirim E, Kosar T. End-to-end data-flow parallelism for throughput optimization in high-speed networks. Journal of Grid Computing. 2012; 10(3):395–418.
- Zaghloul SS. The mutual effect of virtualization and parallelism in a cloud environment. Conference AFRICON;
- Sep 9-12.
- Kim J, Yildirim E, Kosar T. A highly-accurate and low-overhead prediction model for transfer throughput optimization. Proceedings of ACM SC’12 DISCS Workshop; 2012.
- Choi KM, Huh E, Choo H. Efficient resource management scheme of tcp buffer tuned parallel stream to optimize system performance. Proc Embedded and Ubiquitous Computing; Nagasaki, Japan. 2005 Dec.
- AnuKarpaga S, Muralidharan D. High throughput pipelining NoC using clumsy flow control. Indian Journal of Science and Technology. 2016 Aug; 9(29). DOI: 10.17485/ ijst/2016/v9i29/91236.
- Varthini S, Muthaiah R. Digital infinite impulse response filter with floating point multiply accumulate circuit using pipelining. Indian Journal of Science and Technology. 2016 Aug; 9(29). DOI: 10.17485/ijst/2016/v9i29/90907.
- Thiriveni GV, M. Ramakrishnan M. Distributed clustering based energy efficient routing algorithm for heterogeneous wireless sensor networks. Indian Journal of Science and Technology. 2016 Jan; 9(3). DOI: 10.17485/ijst/2016/ v9i3/80493.
- Sasikumar R, Ananthanarayanan V, Rajeswari A. An intelligent pico cell range expansion technique for heterogeneous wireless networks. Indian Journal of Science and Technology. 2016 Mar; 9(9). DOI: 10.17485/ijst/2016/v9i9/67610.
- Bagheri R, Jahanshahi M. Scheduling workflow applications on the heterogeneous cloud resources. Indian Journal of Science and Technology. 2015 Jun; 8(12). DOI: 10.17485/ ijst/2015/v8i12/57984.
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