Dual-Code Bounds on Multiple Concurrent (Local) Data Recovery

Gianira N. Alfarano; Alberto Ravagnani; Emina Soljanin

doi:10.1109/ISIT50566.2022.9834616

Dual-Code Bounds on Multiple Concurrent (Local) Data Recovery

Gianira N. Alfarano, Alberto Ravagnani, Emina Soljanin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We are concerned with linear redundancy storage schemes regarding their ability to provide concurrent (local) recovery of multiple data objects. This paper initiates a study of such systems within the classical coding theory. We show how we can use the structural properties of the generator matrix defining the scheme to obtain a bounding polytope for the set of data access rates the system can support. We derive two dual distance outer bounds, which are sharp for some large classes of matrix families.

Original language	English (US)
Title of host publication	2022 IEEE International Symposium on Information Theory, ISIT 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2613-2618
Number of pages	6
ISBN (Electronic)	9781665421591
DOIs	https://doi.org/10.1109/ISIT50566.2022.9834616
State	Published - 2022
Externally published	Yes
Event	2022 IEEE International Symposium on Information Theory, ISIT 2022 - Espoo, Finland Duration: Jun 26 2022 → Jul 1 2022

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
Volume	2022-June
ISSN (Print)	2157-8095

Conference

Conference	2022 IEEE International Symposium on Information Theory, ISIT 2022
Country/Territory	Finland
City	Espoo
Period	6/26/22 → 7/1/22

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Information Systems
Modeling and Simulation
Applied Mathematics

Access to Document

10.1109/ISIT50566.2022.9834616

Cite this

Alfarano, G. N., Ravagnani, A., & Soljanin, E. (2022). Dual-Code Bounds on Multiple Concurrent (Local) Data Recovery. In 2022 IEEE International Symposium on Information Theory, ISIT 2022 (pp. 2613-2618). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2022-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT50566.2022.9834616

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title = "Dual-Code Bounds on Multiple Concurrent (Local) Data Recovery",

abstract = "We are concerned with linear redundancy storage schemes regarding their ability to provide concurrent (local) recovery of multiple data objects. This paper initiates a study of such systems within the classical coding theory. We show how we can use the structural properties of the generator matrix defining the scheme to obtain a bounding polytope for the set of data access rates the system can support. We derive two dual distance outer bounds, which are sharp for some large classes of matrix families.",

author = "Alfarano, {Gianira N.} and Alberto Ravagnani and Emina Soljanin",

note = "Funding Information: G. N. Alfarano is supported by Swiss Science Foundation grant n. 188430. A. Ravagnani is supported by Dutch Research Council grant VI.Vidi.203.045. E. Soljanin is in part supported by NSF Award CIF-2122400. Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Symposium on Information Theory, ISIT 2022 ; Conference date: 26-06-2022 Through 01-07-2022",

year = "2022",

doi = "10.1109/ISIT50566.2022.9834616",

language = "English (US)",

series = "IEEE International Symposium on Information Theory - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2613--2618",

booktitle = "2022 IEEE International Symposium on Information Theory, ISIT 2022",

address = "United States",

}

Alfarano, GN, Ravagnani, A & Soljanin, E 2022, Dual-Code Bounds on Multiple Concurrent (Local) Data Recovery. in 2022 IEEE International Symposium on Information Theory, ISIT 2022. IEEE International Symposium on Information Theory - Proceedings, vol. 2022-June, Institute of Electrical and Electronics Engineers Inc., pp. 2613-2618, 2022 IEEE International Symposium on Information Theory, ISIT 2022, Espoo, Finland, 6/26/22. https://doi.org/10.1109/ISIT50566.2022.9834616

Dual-Code Bounds on Multiple Concurrent (Local) Data Recovery. / Alfarano, Gianira N.; Ravagnani, Alberto; Soljanin, Emina.
2022 IEEE International Symposium on Information Theory, ISIT 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 2613-2618 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2022-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N1 - Funding Information: G. N. Alfarano is supported by Swiss Science Foundation grant n. 188430. A. Ravagnani is supported by Dutch Research Council grant VI.Vidi.203.045. E. Soljanin is in part supported by NSF Award CIF-2122400. Publisher Copyright: © 2022 IEEE.

PY - 2022

Y1 - 2022

N2 - We are concerned with linear redundancy storage schemes regarding their ability to provide concurrent (local) recovery of multiple data objects. This paper initiates a study of such systems within the classical coding theory. We show how we can use the structural properties of the generator matrix defining the scheme to obtain a bounding polytope for the set of data access rates the system can support. We derive two dual distance outer bounds, which are sharp for some large classes of matrix families.

AB - We are concerned with linear redundancy storage schemes regarding their ability to provide concurrent (local) recovery of multiple data objects. This paper initiates a study of such systems within the classical coding theory. We show how we can use the structural properties of the generator matrix defining the scheme to obtain a bounding polytope for the set of data access rates the system can support. We derive two dual distance outer bounds, which are sharp for some large classes of matrix families.

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M3 - Conference contribution

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T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 2613

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BT - 2022 IEEE International Symposium on Information Theory, ISIT 2022

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ER -

Dual-Code Bounds on Multiple Concurrent (Local) Data Recovery

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