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The Experts below are selected from a list of 57 Experts worldwide ranked by ideXlab platform

Venkatesan Guruswami - One of the best experts on this subject based on the ideXlab platform.

  • an exponential lower bound on the sub packetization of msr codes
    Symposium on the Theory of Computing, 2019
    Co-Authors: Omar Alrabiah, Venkatesan Guruswami
    Abstract:

    An (n,k,l)-vector MDS code is a F-linear subspace of (Fl)n (for some field F) of dimension kl, such that any k (vector) symbols of the codeword suffice to determine the remaining r=n−k (vector) symbols. The length l of each codeword symbol is called the Sub-Packetization of the code. Such a code is called minimum storage regenerating (MSR), if any single symbol of a codeword can be recovered by downloading l/r field elements (which is known to be the least possible) from each of the other symbols. MSR codes are attractive for use in distributed storage systems, and by now a variety of ingenious constructions of MSR codes are available. However, they all suffer from exponentially large Sub-Packetization l ≳ rk/r. Our main result is an almost tight lower bound showing that for an MSR code, one must have l ≥ exp(Ω(k/r)). Previously, a lower bound of ≈ exp(√k/r), and a tight lower bound for a restricted class of ”optimal access” MSR codes, were known. Our work settles a central open question concerning MSR codes that has received much attention. Further our proof is really short, hinging on one Key Definition that is somewhat inspired by Galois theory.

  • an exponential lower bound on the sub packetization of msr codes
    arXiv: Information Theory, 2019
    Co-Authors: Omar Alrabiah, Venkatesan Guruswami
    Abstract:

    An $(n,k,\ell)$-vector MDS code is a $\mathbb{F}$-linear subspace of $(\mathbb{F}^\ell)^n$ (for some field $\mathbb{F}$) of dimension $k\ell$, such that any $k$ (vector) symbols of the codeword suffice to determine the remaining $r=n-k$ (vector) symbols. The length $\ell$ of each codeword symbol is called the sub-packetization of the code. Such a code is called minimum storage regenerating (MSR), if any single symbol of a codeword can be recovered by downloading $\ell/r$ field elements (which is known to be the least possible) from each of the other symbols. MSR codes are attractive for use in distributed storage systems, and by now a variety of ingenious constructions of MSR codes are available. However, they all suffer from exponentially large sub-packetization $\ell \gtrsim r^{k/r}$. Our main result is an almost tight lower bound showing that for an MSR code, one must have $\ell \ge \exp(\Omega(k/r))$. Previously, a lower bound of $\approx \exp(\sqrt{k/r})$, and a tight lower bound for a restricted class of "optimal access" MSR codes, were known. Our work settles a central open question concerning MSR codes that has received much attention. Further our proof is really short, hinging on one Key Definition that is somewhat inspired by Galois theory.

Omar Alrabiah - One of the best experts on this subject based on the ideXlab platform.

  • an exponential lower bound on the sub packetization of msr codes
    Symposium on the Theory of Computing, 2019
    Co-Authors: Omar Alrabiah, Venkatesan Guruswami
    Abstract:

    An (n,k,l)-vector MDS code is a F-linear subspace of (Fl)n (for some field F) of dimension kl, such that any k (vector) symbols of the codeword suffice to determine the remaining r=n−k (vector) symbols. The length l of each codeword symbol is called the Sub-Packetization of the code. Such a code is called minimum storage regenerating (MSR), if any single symbol of a codeword can be recovered by downloading l/r field elements (which is known to be the least possible) from each of the other symbols. MSR codes are attractive for use in distributed storage systems, and by now a variety of ingenious constructions of MSR codes are available. However, they all suffer from exponentially large Sub-Packetization l ≳ rk/r. Our main result is an almost tight lower bound showing that for an MSR code, one must have l ≥ exp(Ω(k/r)). Previously, a lower bound of ≈ exp(√k/r), and a tight lower bound for a restricted class of ”optimal access” MSR codes, were known. Our work settles a central open question concerning MSR codes that has received much attention. Further our proof is really short, hinging on one Key Definition that is somewhat inspired by Galois theory.

  • an exponential lower bound on the sub packetization of msr codes
    arXiv: Information Theory, 2019
    Co-Authors: Omar Alrabiah, Venkatesan Guruswami
    Abstract:

    An $(n,k,\ell)$-vector MDS code is a $\mathbb{F}$-linear subspace of $(\mathbb{F}^\ell)^n$ (for some field $\mathbb{F}$) of dimension $k\ell$, such that any $k$ (vector) symbols of the codeword suffice to determine the remaining $r=n-k$ (vector) symbols. The length $\ell$ of each codeword symbol is called the sub-packetization of the code. Such a code is called minimum storage regenerating (MSR), if any single symbol of a codeword can be recovered by downloading $\ell/r$ field elements (which is known to be the least possible) from each of the other symbols. MSR codes are attractive for use in distributed storage systems, and by now a variety of ingenious constructions of MSR codes are available. However, they all suffer from exponentially large sub-packetization $\ell \gtrsim r^{k/r}$. Our main result is an almost tight lower bound showing that for an MSR code, one must have $\ell \ge \exp(\Omega(k/r))$. Previously, a lower bound of $\approx \exp(\sqrt{k/r})$, and a tight lower bound for a restricted class of "optimal access" MSR codes, were known. Our work settles a central open question concerning MSR codes that has received much attention. Further our proof is really short, hinging on one Key Definition that is somewhat inspired by Galois theory.

C. Jaco Klok - One of the best experts on this subject based on the ideXlab platform.

Shi Pei-sha - One of the best experts on this subject based on the ideXlab platform.

Graeme Mackenzie - One of the best experts on this subject based on the ideXlab platform.