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A method for enhancing end-to-end transfer efficiency via performance tuning factors on dedicated circuit networks with a public cloud platform

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Abstract

There has been a great deal of recent research interest regarding the storage and utilization of big data via remote cloud platforms. The efficiency of large data transfers from remote cloud platforms is a critical issue, and dedicated networks are used for data transfer. To resolve the data transfer efficiency issue, it is necessary to tune the L2-related performance items in the transport equipment and to regulate performance factors, such as window size, between IP layer servers, during the configuration of an end-to-end research network. It is also necessary to tune factor values related to performance items in transport equipment. System level kernel parameter tuning is also needed and results in improved throughput. Here, we measure throughput according to L2-related tuning factors and IP levels, including kernel parameter turning, and present an analysis of the measurement results. The experimental results show that end-to-end servers with tuned factors, in addition to system level kernel parameter tuning, can effectively utilize the available bandwidth.

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References

  1. Dart E, Rotman L, Tierney B, Hester M, Zurawski J (2014) The science DMZ: a network design pattern for data. Sci Program 22(2):173–185

  2. Monga I, Pouyoul E, Guok C (2012) Software-defined networking for big-data science-architectural models from campus to the WAN. In: Proceedings of SCC, Salt Lake City, UT

  3. Maity S, Park J (2016) Powering IoT devices: a novel design and analysis technique. J Converg 7(2):1–10

  4. Azodolmolky S, Wieder P, Yahyapour R, Rollins S (2013) Cloud computing networking: challenges and opportunities for innovations. IEEE Commun Mag 51(7):54–62

    Article  Google Scholar 

  5. Vogel A, Griebler D, Schepke C, Fernandes LG (2017) An intra-cloud networking performance evaluation on cloudstack environment. In: Proceedings of PDP

  6. Alexey G, Parygin DS, Finogeev AA (2017) The convergence computing model for big sensor data mining and knowledge discovery. Hum Centric Comput Inf Sci 7(1):11

    Article  Google Scholar 

  7. Kar J, Mishra MR (2016) Mitigating Threats and security metrics in cloud computing. J Inf Process Syst 12(2):133–226

    Google Scholar 

  8. Banerjee N, Sorber J, Corner M, Rollins S, Ganesan D (2005) Triage: a power-aware software architecture for tiered microservers. Technical report. University of Massachusetts-Amherst, pp 5–22

  9. Burns B, Brock O, Levine BN (2005) MV routing and capacity building in disruption tolerant networks. In: Proceedings of IEEE INFOCOM, pp 398–408

  10. Qiu L, Chandra R, Jain K, Mahdian M (2004) Optimizing the placement of integration points in multi-hop wireless networks. In: Proceedings of ICNP, pp 271–282

  11. Liu JB, Mannemela P (2005) Internet2 end to end performance tuning for distributed computing applications. In: Proceedings of ICIT

  12. Huang J, Wang J, Zhang T, Chen J, Pan Y (2016) Tuning the aggressive TCP behavior for highly concurrent HTTP connections in data center. In: Proceedings of ICDCS

  13. Kailbach W, Ilchmann F (2010) Multi service OTN design and optimization of a Germany wide scale example network. In: Proceedings of Photonic Networks

  14. Heinanen J, Guerin R (1999) A two rate three color marker. RFC 2698

  15. Luo J, Yang X, Xu J, Sun J (2016) AAIC: adaptive-sliding-connection-window solution to TCP incast from application layer. IEEE Commun Lett 20(10):1967–1970

  16. Jung H, Kim S, Yeom H, Kang S, Libman L (2015) Adaptive delay-based congestion control for high bandwidth-delay product networks. In: Proceedings of INFOCOM

  17. Yue Z, Zhang X, Ren Y, Li J, Zhong Q (2012) The performance evaluation and comparison of TCP-based high-speed transport protocols. In: Proceedings of ICSESS

  18. Liu A, Wu B, Hao Y, Zhao N, Yin H (2011) Design and development of adaptive-generalized optical transceiver module with multi-rates supporting SONET, SDH and Gigabit-Ethernet, In: Proceedings of OECC

  19. Hamad A, Kadoch M (2015) SONET over Ethernet. In: Proceedings of GOCICT

  20. Jimenez T, Lopez V, Jimenez F, Dios OG, Fernandez-Palacios JP (2016) Techno-economic evaluation of optical transport network in metropolitan deployments. In: Proceedings of ECOC

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Authors and Affiliations

  1. Korea Institute of Science and Technology Information, Daejeon, Korea

    Won-Hyuk Lee, Jong-Seon Park, Seung-Hae Kim & Jin-Hyung Park

  2. Daegu Catholic University, Gyeongsan, Korea

    Joon-Min Gil

Authors
  1. Won-Hyuk Lee
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  2. Jong-Seon Park
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  3. Seung-Hae Kim
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  4. Jin-Hyung Park
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  5. Joon-Min Gil
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Corresponding author

Correspondence to Joon-Min Gil.

Additional information

This research was supported by Korea Institute of Science and Technology Information (KISTI).

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Lee, WH., Park, JS., Kim, SH. et al. A method for enhancing end-to-end transfer efficiency via performance tuning factors on dedicated circuit networks with a public cloud platform. J Supercomput 74, 1255–1266 (2018). https://doi.org/10.1007/s11227-017-2157-9

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  • DOI: https://doi.org/10.1007/s11227-017-2157-9

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