Open Access
Issue
E3S Web Conf.
Volume 412, 2023
International Conference on Innovation in Modern Applied Science, Environment, Energy and Earth Studies (ICIES’11 2023)
Article Number 01090
Number of page(s) 14
DOI https://doi.org/10.1051/e3sconf/202341201090
Published online 17 August 2023
  1. V. Belov, A. Tatarintsev, and E. Nikulchev, ―Comparative Characteristics of Big Data Storage Formats,‖ Journal of Physics Conference Series, vol. 1727, p. 012005, Jan. 2021, doi: 10.1088/1742-6596/1727/1/012005. [CrossRef] [Google Scholar]
  2. A. Gusev, D. Ilin, and E. Nikulchev, ―The Dataset of the Experimental Evaluation of Software Components for Application Design Selection Directed by the Artificial Bee Colony Algorithm,‖ Data, vol. 5, no. 3, Art. no. 3, Sep. 2020, doi: 10.3390/data5030059. [CrossRef] [Google Scholar]
  3. G. Petushkov, ―Evaluation and reliability prediction for highly reliable software and hardware systems: The case of data processing centers,‖ Russian Technological Journal, vol. 8, pp. 21–26, Mar. 2020, doi: 10.32362/2500-316X-2020-8-1-21-26. [CrossRef] [Google Scholar]
  4. M. Chen, S. Mao, and Y. Liu, ―Big Data: A Survey,‖ Mob. Netw. Appl., vol. 19, no. 2, pp. 171–209, Apr. 2014, doi: 10.1007/s11036-013-0489-0. [CrossRef] [Google Scholar]
  5. P. Russom, ―Big data analytics,‖ TDWI best practices report, fourth quarter, vol. 19, no. 4, pp. 1–34, 2011. [Google Scholar]
  6. ―Cloudera administration handbook.‖ https://text.123docz.net/document/5338213cloudera-administration-handbook-rohit-menon-5-pdf.htm (accessed Oct. 21, 2021). [Google Scholar]
  7. ―HortonWorks Data Platform : new book,‖ 2015. [Google Scholar]
  8. T. Dunning and E. Friedman, Real-World Hadoop. O’Reilly Media, Inc., 2015. [Google Scholar]
  9. D. Quintero et al., Implementing an IBM InfoSphere BigInsights Cluster using Linux on Power, First edition. in IBM redbooks. IBM, International Technical Support Organization, 2015. [Google Scholar]
  10. ―Pivotal HD Enterprise 1.1 Installation and Administrator | Manualzz,‖ manualzz.com. https://manualzz.com/doc/25974984/pivotal-hd-enterprise-1.1installation-and-administrator (accessed Aug. 07, 2022). [Google Scholar]
  11. D. Sarkar, ―Pro Microsoft HDInsight : Hadoop on Windows /,‖ 2014. [CrossRef] [Google Scholar]
  12. J. Moorthy et al., ―Big Data: Prospects and Challenges,‖ Vikalpa:The Journal for Decision Makers, vol. 40, pp. 74–96, Mar. 2015, doi: 10.1177/0256090915575450. [CrossRef] [Google Scholar]
  13. Z. Ping et al., ―Carbon-based archiving: current progress and future prospects of DNA-based data storage,‖ GigaScience, vol. 8, no. 6, p. giz075, Jun. 2019, doi: 10.1093/gigascience/giz075. [CrossRef] [PubMed] [Google Scholar]
  14. M. Castillo, ―From Hard Drives to Flash Drives to DNA Drives,‖ AJNR. American journal of neuroradiology, vol. 35, Apr. 2013, doi: 10.3174/ajnr.A3482. [Google Scholar]
  15. R. Appuswamy et al., ―OligoArchive: Using DNA in the DBMS storage hierarchy,‖ in CIDR, 2019. [Google Scholar]
  16. M. E. Allentoft et al., ―The half-life of DNA in bone: measuring decay kinetics in 158 dated fossils,‖ Proceedings of the Royal Society B: Biological Sciences, vol. 279, no. 1748, pp. 4724–4733, Dec. 2012, doi: 10.1098/rspb.2012.1745. [CrossRef] [PubMed] [Google Scholar]
  17. R. N. Grass, R. Heckel, M. Puddu, D. Paunescu, and W. J. Stark, ―Robust chemical preservation of digital information on DNA in silica with error-correcting codes,‖ Angew Chem Int Ed Engl, vol. 54, no. 8, pp. 2552–2555, Feb. 2015, doi: 10.1002/anie.201411378. [CrossRef] [PubMed] [Google Scholar]
  18. R. Heckel, G. Mikutis, and R. N. Grass, ―A Characterization of the DNA Data Storage Channel,‖ Sci Rep, vol. 9, no. 1, p. 9663, Dec. 2019, doi: 10.1038/s41598019-45832-6. [CrossRef] [PubMed] [Google Scholar]
  19. C. Roy, M. Pandey, and S. SwarupRautaray, ―A Proposal for Optimization of Data Node by Horizontal Scaling of Name Node Using Big Data Tools,‖ in 2018 3rd International Conference for Convergence in Technology (I2CT), Pune: IEEE, Apr. 2018, pp. 1–6. doi: 10.1109/I2CT.2018.8529795. [Google Scholar]
  20. J. D. Watson and F. H. C. Crick, ―THE CLASSIC: Molecular Structure of Nucleic Acids: A Structure for Deoxyribose Nucleic Acid,‖ Clinical Orthopaedics and Related Research®, vol. 462, pp. 3–5, Sep. 2007, doi: 10.1097/BLO.0b013e31814b9304. [CrossRef] [PubMed] [Google Scholar]
  21. M. Neiman, ―Some fundamental issues of microminiaturization,‖ Radiotekhnika, vol. 1, pp. 3–12, 1964. [Google Scholar]
  22. M. Neiman, ―On the molecular memory systems and the directed mutations,‖ Radiotekhnika, vol. 6, pp. 1–8, 1965. [Google Scholar]
  23. J. Davis, ―Microvenus,‖ Art Journal, vol. 55, no. 1, pp. 70–74, Mar. 1996, doi: 10.1080/00043249.1996.10791743. [CrossRef] [Google Scholar]
  24. D. G. Gibson et al., ―Creation of a bacterial cell controlled by a chemically synthesized genome,‖ Science, vol. 329, no. 5987, pp. 52–56, Jul. 2010, doi: 10.1126/science.1190719. [CrossRef] [PubMed] [Google Scholar]
  25. J. P. Cox, ―Long-term data storage in DNA,‖ Trends Biotechnol, vol. 19, no. 7, pp. 247–250, Jul. 2001, doi: 10.1016/s0167-7799(01)01671-7. [CrossRef] [PubMed] [Google Scholar]
  26. L. Ceze, J. Nivala, and K. Strauss, ―Molecular digital data storage using DNA,‖ Nat Rev Genet, vol. 20, no. 8, pp. 456–466, Aug. 2019, doi: 10.1038/s41576-019-01253. [CrossRef] [PubMed] [Google Scholar]
  27. M. Blawat et al., ―Forward Error Correction for DNA Data Storage,‖ Procedia Computer Science, vol. 80, pp. 1011–1022, Jan. 2016, doi: 10.1016/j.procs.2016.05.398. [CrossRef] [Google Scholar]
  28. G. Church, Y. Gao, and S. Kosuri, ―Next-Generation Digital Information Storage in DNA,‖ Science (New York, N.Y.), vol. 337, p. 1628, Aug. 2012, doi: 10.1126/science.1226355. [CrossRef] [PubMed] [Google Scholar]
  29. N. R. Manar Sais Jaafar Abouchabaka, ―SYNTHETIC DNA AS A SOLUTION TO THE BIG DATA STORAGE PROBLEM,‖ Journal of Theoretical and Applied Information Technology, vol. 99, no. 15, Aug. 2021, doi: 10.5281/zenodo.5353710. [Google Scholar]
  30. M. Sais, N. Rafalia, and J. Abouchabaka, ―Intelligent Approaches to Optimizing Big Data Storage and Management: REHDFS system and DNA Storage,‖ Procedia Computer Science, vol. 201, pp. 746–751, Jan. 2022, doi: 10.1016/j.procs.2022.03.101. [CrossRef] [Google Scholar]
  31. M. T. Barrett et al., ―Comparative genomic hybridization using oligonucleotide microarrays and total genomic DNA,‖ Proc Natl Acad Sci U S A, vol. 101, no. 51, pp. 17765–17770, Dec. 2004, doi: 10.1073/pnas.0407979101. [CrossRef] [PubMed] [Google Scholar]
  32. Z. Chen et al., ―Highly accurate fluorogenic DNA sequencing with information theory–based error correction,‖ Nat Biotechnol, vol. 35, no. 12, Art. no. 12, Dec. 2017, doi: 10.1038/nbt.3982. [Google Scholar]
  33. D. Limbachiya and M. Gupta, ―Natural Data Storage: A Review on sending Information from now to then via Nature,‖ May 2015. [Google Scholar]
  34. B. Alberts, A. Johnson, J. Lewis, M. Raff, K. Roberts, and P. Walter, ―The Structure and Function of DNA,‖ Molecular Biology of the Cell. 4th edition, 2002, Accessed: Jul. 08, 2021. [Online]. Available: https://www.ncbi.nlm.nih.gov/books/NBK26821/ [Google Scholar]
  35. Y. Erlich and D. Zielinski, ―DNA Fountain enables a robust and efficient storage architecture,‖ Synthetic Biology, preprint, Sep. 2016. doi: 10.1101/074237. [Google Scholar]
  36. F. Sanger and A. R. Coulson, ―A rapid method for determining sequences in DNA by primed synthesis with DNA polymerase,‖ J Mol Biol, vol. 94, no. 3, pp. 441–448, May 1975, doi: 10.1016/0022-2836(75)90213-2. [Google Scholar]
  37. B. Li, L. Ou, and D. Du, ―IMG-DNA: Approximate DNA Storage for Images,‖ Mar. 2021, doi: 10.1145/3456727.3463771. [Google Scholar]
  38. A. Lenz, P. H. Siegel, A. Wachter-Zeh, and E. Yaakobi, ―Coding Over Sets for DNA Storage,‖ IEEE Trans. Inform. Theory, vol. 66, no. 4, pp. 2331–2351, Apr. 2020, doi: 10.1109/TIT.2019.2961265. [CrossRef] [Google Scholar]
  39. C. Bancroft, T. Bowler, B. T, and C. T. Clelland, ―Long-term storage of information in DNA,‖ Science, vol. 293, no. 5536, pp. 1763–1765, Sep. 2001, doi: 10.1126/science.293.5536.1763c. [CrossRef] [Google Scholar]
  40. S. Kosuri and Church, ―Large-scale de novo DNA synthesis: technologies and applications,‖ Nat Methods, vol. 11, no. 5, pp. 499–507, May 2014, doi: 10.1038/nmeth.2918. [CrossRef] [PubMed] [Google Scholar]
  41. S. M. H. Tabatabaei Yazdi, Y. Yuan, J. Ma, H. Zhao, and O. Milenkovic, ―A Rewritable, Random-Access DNA-Based Storage System,‖ Sci Rep, vol. 5, no. 1, p. 14138, Sep. 2015, doi: 10.1038/srep14138. [CrossRef] [PubMed] [Google Scholar]
  42. R. W. Hamming, ―Error Detecting and Error Correcting Codes,‖ Bell System Technical Journal, vol. 29, no. 2, pp. 147–160, 1950, doi: 10.1002/j.15387305.1950.tb00463.x. [CrossRef] [Google Scholar]
  43. L. Organick et al., ―Random access in large-scale DNA data storage,‖ Nat Biotechnol, vol. 36, no. 3, pp. 242–248, Mar. 2018, doi: 10.1038/nbt.4079. [CrossRef] [PubMed] [Google Scholar]
  44. J. Bonnet et al., ―Chain and conformation stability of solid-state DNA: implications for room temperature storage,‖ Nucleic Acids Res, vol. 38, no. 5, pp. 1531–1546, Mar. 2010, doi: 10.1093/nar/gkp1060. [CrossRef] [PubMed] [Google Scholar]
  45. L. M. Adleman, ―Molecular computation of solutions to combinatorial problems,‖ Science, vol. 266, no. 5187, pp. 1021–1024, Nov. 1994, doi: 10.1126/science.7973651. [CrossRef] [PubMed] [Google Scholar]
  46. A. Ahmadpour and A. Ahadpour Shal, A Novel Formulation of Hamming Code. 2009. doi: 10.1109/ECTICON.2009.5137169. [Google Scholar]
  47. S. B. Wicker, Error Control Systems for Digital Communication and Storage, US e. édition. Englewood Cliffs, NJ: Pearson, 1994. [Google Scholar]
  48. M. W. Azhar, T. T. Hoang, and P. Larsson-Edefors, ―Cyclic Redundancy Checking (CRC) Accelerator for the FlexCore Processor,‖ in 2010 13th Euromicro Conference on Digital System Design: Architectures, Methods and Tools, Sep. 2010, pp. 675–680. doi: 10.1109/DSD.2010.51. [CrossRef] [Google Scholar]

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