Effective Local Reconstruction Codes Based on Regeneration for Large-Scale Storage Systems

  • Quanqing XuEmail author
  • Hong Wai Ng
  • Weiya Xi
  • Chao Jin
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 887)


We introduce Regenerating-Local Reconstruction Codes (R-LRC) and describe their encoding and decoding techniques in this paper. After that their repair bandwidths of different failure patterns are investigated. We also explore an alternative of R-LRC, which gives R-LRC lower repair bandwidth. Since R-LRC is an extended version of Pyramid codes, optimization of repair bandwidth of a single failure will also apply to R-LRC. Compared with Pyramid Codes, Regenerating-Local Reconstruction Codes have two benefits: (1) In an average, they use around 2.833 blocks in repairing 2 failures while the Pyramid codes use about 3.667 blocks. Hence, they have lower IOs than Pyramid Codes. (2) When there are 2 failures occurring at common block group and special block group, they require only around M/2, which is lower compared with M in Pyramid codes when k ≥ 2. In addition, we present an efficient interference alignment mechanism in R-LRC, which performs algebraic alignment so that the useless and unwanted dimension is decreased. Therefore, the network bandwidth consumption is reduced.


Local reconstruction codes Regeneration code Interference alignment Maximum distance separable 


  1. 1.
    Huang, C., Simitci, H., Xu, Y., Ogus, A., Calder, B., Gopalan, P., Li, J., Yekhanin, S.: Erasure coding in windows azure storage. In: 2012 USENIX Annual Technical Conference, pp. 15–26Google Scholar
  2. 2.
    Sathiamoorthy, M., Asteris, M., Papailiopoulos, D.S., Dimakis, A.G., Vadali, R., Chen, S., Borthakur, D.: Xoring elephants: novel erasure codes for big data. PVLDB 6(5), 325–336 (2013)Google Scholar
  3. 3.
    Rashmi, K.V., Shah, N.B., Gu, D., Kuang, H., Borthakur, D., Ramchandran, K.: A “hitchhiker’s” guide to fast and efficient data reconstruction in erasure-coded data centers. In: ACM SIGCOMM 2014 Conference, pp. 331–342 (2014)Google Scholar
  4. 4.
    Ford, D., Labelle, F., Popovici, F.I., Stokely, M., Truong, V., Barroso, L., Grimes, C., Quinlan, S.: Availability in globally distributed storage systems. In: OSDI 2010, pp. 61–74 (2010)Google Scholar
  5. 5.
    Xu, Q., Arumugam, R.V., Yong, K.L., Mahadevan, S.: Efficient and scalable metadata management in EB-scale file systems. IEEE Trans. Parallel Distrib. Syst. 25(11), 2840–2850 (2014)CrossRefGoogle Scholar
  6. 6.
    Dimakis, A.G., Godfrey, B., Wu, Y., Wainwright, M.J., Ramchandran, K.: Network coding for distributed storage systems. IEEE Trans. Inf. Theory 56(9), 4539–4551 (2010)CrossRefGoogle Scholar
  7. 7.
    Li, R., Lin, J., Lee, P.P.C.: CORE: augmenting regenerating coding-based recovery for single and concurrent failures in distributed storage systems. In: Proceedings of IEEE Conference on Mass Storage Systems and Technologies (MSST 2013) (2013)Google Scholar
  8. 8.
    Duminuco, A., Biersack, E.: A practical study of regenerating codes for peer-to-peer backup systems. In: 29th IEEE International Conference on Distributed Computing Systems (ICDCS 2009), pp. 376–384 (2009)Google Scholar
  9. 9.
    Hu, Y., Chen, H.C.H., Lee, P.P.C., Tang, Y.: Nccloud: applying network coding for the storage repair in a cloud-of-clouds. In: FAST 2012, p. 21 (2012)Google Scholar
  10. 10.
    Gopalan, P., Huang, C., Simitci, H., Yekhanin, S.: On the locality of codeword symbols. IEEE Trans. Inf. Theory 58(11), 6925–6934 (2011)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Huang, C., Chen, M., Li, J.: Pyramid codes: flexible schemes to trade space for access efficiency in reliable data storage systems. TOS 9(1), 3 (2013)CrossRefGoogle Scholar
  12. 12.
    Xu, Q., Xi, W., Yong, K.L., Jin, C.: Concurrent regeneration code with local reconstruction in distributed storage systems. In: The 9th International Conference on Multimedia and Ubiquitous Engineering, pp. 415–422 (2015)Google Scholar
  13. 13.
    Kamath, G.M., Prakash, N., Lalitha,V., Kumar, P.V.: Codes with local regeneration. In: Proceedings of the IEEE International Symposium on Information Theory (ISIT), Istanbul, Turkey, pp. 1606–1610, July 2013Google Scholar
  14. 14.
    Rawat, A.S., Koyluoglu, O.O., Silberstein, N., Vishwanath, S.: Secure locally repairable codes for distributed storage systems. In: Proceedings of the IEEE International Symposium on Information Theory (ISIT), pp. 2224–2228 (2013)Google Scholar
  15. 15.
    Wu, Y., Dimakis, A.G.: Reducing repair traffic for erasure coding-based storage via interference alignment. In: IEEE International Symposium on Information Theory, ISIT 2009, Seoul, Korea, Proceedings, 28 June–3 July 2009, pp. 2276–2280. IEEE (2009)Google Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Data Storage Institute, A*STARSingaporeSingapore
  2. 2.Nanyang Technological UniversitySingaporeSingapore
  3. 3.Institute of High Performance Computing, A*STARSingaporeSingapore

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