Abstract
The use of a distributed storage system (DSS), in a network with a large number of interconnected nodes, can increase significantly the storage efficiency. The main issues in this area are the reconstruction process or obtaining the entire original message out of the DSS and the repair process or recovering the lost stored data of a failed node. Finding an adequate code that will manage successfully both processes, to have an efficient system, is a challenge. Many codes for data distribution are in play. Finding a good code (good encoding procedure), one which achieves better performance, require choosing ways to make a fair comparison among codes. In this paper, we are proposing a way to compare two DSS codes by examining the system parameters. We conclude by comparing three different class of codes: Repetition, Reed-Solomon and Regenerating codes and deciding which one is the most efficient.
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References
Moon, T.K.: Error Correction Coding: Mathematical Methods and Algorithms, 1 edn. Wiley-Interscience (2005)
Weatherspoon, H., Kubiatowicz, J.: Erasure coding vs. replication: a quantitative comparison. In: Proceedings of 1st International Workshop Peer-to-Peer System (IPTPS), pp. 328–338 (2007)
Memorandum of understanding for the implementation of the COST Action “European Cooperation for Statistics of Network Data Science” (2015)
Rashmi, K.V., Shah, N.B., Kumar, P.V.: Regenerating codes for errors and erasures in distributed storage. In: Proceedings of IEEE International Symposium on Information Theory (ISIT) (2012)
Dimakis, A.G., Prabhakaran, V., Ramchandran, K.: Decentralized erasure code for distributed networked storage. IEEE/ACM Trans. Netw. 14, 2809 (2006)
Rawat, A.S., Koyluoglu, O.O., Silberstein, N., Vishwanath, S.: Optimal locally repairable and secure codes for distributed storage system. IEEE Trans. Inf. Theory 60, 212–236 (2013)
Dimakis, A.G., Godfrey, P.B., Wainright, M., Ramchadran, K.: Network coding for distributed storage systems. In: Proceedings of the 26th IEEE International Conference on Computer Communications, Anchorage, AK, pp. 2000–2008, May 2007
Dimakis, A.G., Godfrey, P.B., Wu, Y., Wainright, M.J., Ramchandran, K.: Network coding for distributed storage systems. IEEE Trans. Inf. Theory 57(8), 5227–5239 (2011)
Rashmi, K.V., Shah, N.B., Kumar, P.V.: Optimal exact-regenerating codes for distributed storage at the MSR and MBR points via a product-Matrix Construction. IEEE Trans. Inf. Theory 57(8), 5227–5239 (2011)
Paunkoska, N., Finamore, W., Karamachoski, J., Puncheva, M., Marina, N.: Improving DSS efficiency with shortened MSR codes. In: ICUMT (2016)
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Paunkoska, N., Finamore, W.A., Marina, N. (2019). Fair Comparison of DSS Codes. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, vol 886. Springer, Cham. https://doi.org/10.1007/978-3-030-03402-3_6
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DOI: https://doi.org/10.1007/978-3-030-03402-3_6
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