Minimum Bandwidth Regenerating Codes Based on Cyclic VFR Codes = Minimum Bandwidth Regenerating Codes Based on Cyclic VFR Codes

다국어 초록 (Multilingual Abstract)

In order to improve the reliability and repair efficiency of distributed storage systems, minimum bandwidth regenerating (MBR) codes based on cyclic variable fractional repetition (VFR) codes are constructed in this thesis, which can repair failed nodes accurately. Specifically, in order to consider the imbalance of data accessed by the users, cyclic VFR codes are constructed according to that data with different heat degrees are copied in different repetition degrees. Moreover, we divide the storage nodes into groups, and construct MBR codes based on cyclic VFR codes to improve the file download speed. Performance analysis and simulation results show that, the repair locality of a single node failure is always 2 when MBR codes based on cyclic VFR codes are adopted in distributed storage systems, which is obviously superior to the traditional MBR codes. Compared with RS codes and simple regenerating codes, the proposed MBR codes based on cyclic VFR codes have lower repair locality, repair complexity and bandwidth overhead, as well as higher repair efficiency. Moreover, relative to FR codes, the MBR codes based on cyclic VFR codes can be applicable to more storage systems.

참고문헌 (Reference)

1 M. F. Aktas, "Simplex queues for hot-data download" 45 (45): 35-36, 2017

2 D. S. Papailiopoulos, "Simple regenerating codes: network coding for cloud storage" 2801-2805, 2012

3 B. Zhu, "Replication-based distributed storage systems with variable repetition degrees" 1-5, 2014

4 K. V. Rashmi, "Optimal exact-regenerating codes for distributed storage at the MSR and MBR points via a product-matrix construction" 57 (57): 5227-5239, 2011

5 C. Li, "On a class of multi-source distributed storage with exact repair" 6 : 20704-20711, 2018

6 R. Ahlswede, "Network information flow" 46 (46): 1204-1216, 2000

7 A. G. Dimakis, "Network coding for distributed storage systems" 56 (56): 4539-4551, 2010

8 A. G. Dimakis, "Network coding for distributed storage systems" 2000-2008, 2007

9 M. Y. Nam, "Locally repairable fractional repetition codes" 128-132, 2015

10 D. S. Papailiopoulos, "Locally repairable codes" 60 (60): 5843-5855, 2014

11 Q. Yu, "Irregular fractional repetition code optimization for heterogeneous cloud storage" 32 (32): 1048-1060, 2014

12 K. V. Rashmi, "Information-theoretically secure erasure codes for distributed storage" 64 (64): 1621-1646, 2018

13 R. Rodrigues, "High availability in DHTs: erasure coding vs. replication" 226-239, 2005

14 B. Zhu, "General fractional repetition codes for distributed storage systems" 18 (18): 660-663, 2014

15 S. E. Rouayheb, "Fractional repetition codes for repair in distributed storage systems" 1510-1517, 2010

16 K. W. Shum, "Existence of minimum-repair-bandwidth cooperative regenerating codes" 1-6, 2011

17 Z. Yuan, "Efficiently coding replicas to erasure coded blocks in distributed storage systems" 21 (21): 1897-1900, 2017

18 N. Bardis, "Effective method to restore data in distributed data storage systems" 1248-1253, 2015

19 K. W. Shum, "Cooperative regenerating codes" 59 (59): 7229-7258, 2013

20 Z. Ullah, "Analytical study on performance, challenges and future considerations of google file system" 3 (3): 279-284, 2014

21 A. Higai, "A study of effective replica reconstruction schemes for the hadoop distributed file system" E98D (E98D): 872-882, 2015

22 B. Wei, "A new adaptive coding selection method for distributed storage systems" 6 : 13350-13357, 2018

23 Emmy Mugisha, "A Reliable Secure Storage Cloud and Data Migration Based on Erasure Code" 한국인터넷정보학회 12 (12): 436-453, 2018