DOI QR코드

DOI QR Code

Analysis on NDN Testbeds for Large-scale Scientific Data: Status, Applications, Features, and Issues

과학 빅데이터를 위한 엔디엔 테스트베드 분석: 현황, 응용, 특징, 그리고 이슈

  • Lim, Huhnkuk (Division of Computer and Information Engineering, Hoseo University) ;
  • Sin, Gwangcheon (Department of Information and security, Hoseo University)
  • Received : 2020.05.30
  • Accepted : 2020.06.10
  • Published : 2020.07.31

Abstract

As the data volumes and complexity rapidly increase, data-intensive science handling large-scale scientific data needs to investigate new techniques for intelligent storage and data distribution over networks. Recently, Named Data Networking (NDN) and data-intensive science communities have inspired innovative changes in distribution and management for large-scale experimental data. In this article, analysis on NDN testbeds for large-scale scientific data such as climate science data and High Energy Physics (HEP) data is presented. This article is the first attempt to analyze existing NDN testbeds for large-scale scientific data. NDN testbeds for large-scale scientific data are described and discussed in terms of status, NDN-based application, and features, which are NDN testbed instance for climate science, NDN testbed instance for both climate science and HEP, and the NDN testbed in SANDIE project. Finally various issues to prevent pitfalls in NDN testbed establishment for large-scale scientific data are analyzed and discussed, which are drawn from the descriptions of NDN testbeds and features on them.

데이터 볼륨과 복잡도가 빠르게 증가함에 따라 과학 빅데이터를 다루는 데이터 집적 과학은 네트워크를 통해 보다 효과적인 데이터 저장 및 분배를 위한 새로운 기술을 발견하는 것을 필요로 한다. 최근 네임드 데이터 네트워킹 커뮤니티와 데이터 집적 과학 커뮤니티는 함께 과학 실험 빅데이터의 분배 및 관리에 있어서 혁신적인 변화를 꾀하였다. 본 논문 에서는 기후과학 및 고에너지물리 데이터 등과 같은 과학 빅데이터를 위한 현존하는 엔디엔 테스트베드들에 대한 분석이 처음으로 이루어진다. 과학 빅데이터를 위한 엔디엔 테스트베드들을 현황, 엔디엔 기반 응용, 특징 측면에서 묘사하고 토의한다. 마지막으로 과학 빅데이터를 위한 엔디엔 테스트베드 네트워크를 확립함에 있어서, 함정에 빠질 수 있는 다양한 이슈들을 엔디엔 테스트베드들에 대한 묘사 그리고 특징들로 부터 도출하여, 분석 제시한다.

Keywords

References

  1. C. Fan, C. Olschanowsky, S. Shannigrahi, C. Papadopoulos, S. DiBenedetto, and H. Newman, "Managing Scientific Data with Named Data Networking," in Proc. 5th Int. Workshop Network Aware Data Manage., pp. 1-7, Nov. 2015.
  2. C. Olschanowsky, S. Shannigrahi, and C. Papadopoulos, "Supporting Climate Research using Named Data Networking," in 20th IEEE Int. Workshop Local and Metropolitan Area Networks, pp. 1-6, May. 2014.
  3. D. Kim, I. Hwang, V. Srivastava, Y.-B. Ko, and H. Lim, "Implementation of a Front-end and Back-end NDN System for Climate Modeling Application," in Inform. and Commun. Technol. Convergence 2015 Int. Conf., pp. 554-559.
  4. H. Lim, A. Ni, D. Kim, and Y.-B. Ko, "Named Data Networking Testbed for Scientific Data," 2nd International Conference on Computer and Communication Systems, pp. 65-69, Jul. 2017.
  5. S. Shannigrahi, A. Barczuk, C. Papadopoulos, A. Sim, I. Monga, H. Newman, and J. Wu, "Named Data Networking in Climate Research and HEP Applications," in 21st Int. Conf. on Computing in High Energy and Nuclear Physics, IOP Publishing. Journal of Physics: Conference Series, vol. 664, pp. 1-8, 2015.
  6. S. Shannigrahi, C. Fan, and C. Papadopoulos, "Request Aggregation, Caching, and Forwarding Strategies for Improving Large Climate Data Distribution with NDN: A Case Study," 2017 Proceedings of Information Centric Networking, pp. 54-65, 2017.
  7. S. Shannigrahi, C. Fan, and C. Papadopoulos, "SCARI: A Strategic Caching and Reservation Protocol for ICN," In Proceedings of the Asian Internet Engineering Conference, pp. 1-8. ACM, 2018.
  8. M. Alhowaidi, B. Ramamurthy, B. Bockelman, and D. Swanson, "The Case for Using Content-Centric Networking for Distributing High Energy Physics Software," in 37th IEEE Int. Conf. on Distributed Computing Systems, pp. 2571-2572, Jun. 2017.
  9. SANDIE [Internet]. Available: https://www.nsf.gov/awardsearch.
  10. H. Lim, A. Ni, D. Kim, Y.-B. Ko, S. Susmit, and C. Papadouplous, "NDN Construction for Big Science: Lessons Learned from Establishing a Testbed," IEEE Network, vol. 32, no. 6, pp. 124-136, Nov. 2018. https://doi.org/10.1109/MNET.2018.1800088
  11. A. Ni, and H. Lim, "A Named Data Networking Testbed with Global NDN Connection," Journal of Korean Institute of Communications and Information Sciences, vol. 40, no. 12, pp. 2419-2426, Dec. 2015. https://doi.org/10.7840/kics.2015.40.12.2419
  12. CMIP5 [Internet]. Available: http://cmip-pcmdi.llnl.gov/cmip5/.
  13. K. Taylor, R. Stouffer, and G. Meehl, "An Overview of CMIP5 and the Experiment Design," Bulletin of the American Meteorological Society, vol. 93, no. 4, pp. 485-498, 2012. https://doi.org/10.1175/BAMS-D-11-00094.1
  14. A. Dorigo, P. Elmer, F. Furano, and A. Hanushevsky. Xrootd-a highly scalable architecture for data access. WSEAS Transactions on Computers, vol. 5, pp. 1-12, 2005.
  15. SANDIE project [Internet]. Available: http://Indico.hep.caltech.edu.
  16. E. Yeh, T. Ho, Y. Cui, M. Burd, Ran Liu, and D. Leong, "VIP: a Framework for Joint Dynamic Forwarding and Caching in Named Data Networks," in Proc. 1st Int. Conf. Information-Centric Networking, pp. 117-126.
  17. NSF project [Internet]. Available: https://grantome.com/grant/NSF/ACI-1659403.
  18. L. Cinquini, D. Crichton, C. Mattmann, J. Harne, and, G. Shipman, "The Earth System Grid Federation (ESGF): An open infrastructure for access to distributed geospatial data," Future Generation Comput. Syst., vol. 36, pp. 400-417, Jul. 2014. https://doi.org/10.1016/j.future.2013.07.002
  19. L. Wang, "Economic Levers for Mitigating Interest Flooding Attack in Named Data Networking," Mathematical Problems in Engineering, vol. 2017, pp. 1-12, Jun. 2017.
  20. Y. Ren, J. Li, S. Shi, L. Li, G. Wang, and B. Zhang, "Congestion Control in Named Data Networking-A Survey," Computer Communications, vol. 86, pp. 1-11, Apr. 2016. https://doi.org/10.1016/j.comcom.2016.04.017
  21. M.-H. Wang, L.-W. Chen, P.-W. Chi, and C.-L. Lei, "SDUDP: A Reliable UDP-Based Transmission Protocol Over SDN," IEEE Access, vol. 5, pp. 5904-5916, May. 2017. https://doi.org/10.1109/ACCESS.2017.2693376