{"id":713446,"date":"2020-12-17T11:42:47","date_gmt":"2020-12-17T19:42:47","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=713446"},"modified":"2022-05-17T21:45:32","modified_gmt":"2022-05-18T04:45:32","slug":"improved-maximally-recoverable-lrcs-using-skew-polynomials","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/improved-maximally-recoverable-lrcs-using-skew-polynomials\/","title":{"rendered":"Improved Maximally Recoverable LRCs using Skew Polynomials"},"content":{"rendered":"

An (n,r,h,a,q)-LRC is a linear code over F_q of length n, whose codeword symbols are partitioned into n\/r local groups each of size r. Each local group satisfies ‘a’ local parity checks to recover from ‘a’ erasures in that local group and there are further h global parity checks to provide fault tolerance from more global erasure patterns. Such an LRC is Maximally Recoverable (MR), if it can correct all erasure patterns which are information-theoretically correctable given this structure—these are precisely patterns with up to ‘a’ erasures in each local group and an additional h erasures anywhere in the codeword.<\/p>\n

We give an explicit construction of (n,r,h,a,q)-MR LRCs with field size q bounded by max{r,n\/r}^{min{h,r-a}}. This significantly improves upon known constructions in most parameter ranges. Moreover, it matches the best known lower bound in an interesting range of parameters where r ~ sqrt{n}, r-a ~ sqrt{n}) and h is a fixed constant with h<= a+2, achieving the optimal field size of\u00a0 ~ n^{h\/2}. Our construction is based on the theory of skew polynomials.<\/p>\n","protected":false},"excerpt":{"rendered":"

An (n,r,h,a,q)-LRC is a linear code over F_q of length n, whose codeword symbols are partitioned into n\/r local groups each of size r. Each local group satisfies ‘a’ local parity checks to recover from ‘a’ erasures in that local group and there are further h global parity checks to provide fault tolerance from more 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