A New Mining Consensus Algorithm: A Binary Matrix Representation Based

Mostefa Kara; Abdelkader Laouid; Mohammad Hammoudeh; Elena Makeeva; Ahcene Bounceur

doi:10.1007/978-3-031-80853-1_36

A New Mining Consensus Algorithm: A Binary Matrix Representation Based

Mostefa Kara, Abdelkader Laouid, Mohammad Hammoudeh, Elena Makeeva^*, Ahcene Bounceur

^*Corresponding author for this work

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

Abstract

Abdelkader et al. recently proposed a new data representation method designed to enable efficient storage and management of diverse data types on the blockchain, guarantee scalability, cost-effectiveness, and network efficiency. They transformed a binary matrix M of dimensions m×n bits into two vectors H and V with sizes m^′ and n^′, respectively. The compression rate given by (m^′+n^′+∣Hash(M)∣)×100(m×n) expands exponentially, i.e., 2^λ with λ depends on m and n), making their technique highly effective for data size reduction. For instance, with a matrix M of size 512×512 bits, they achieved a reduction rate of 96.42%. The conversion from M to (H, V) is both fast and simple. The presented paper uses these parameters to create a new consensus algorithm based on solving the challenge of recovering the original data using H, V, and Hash(M) in order to determine the next miner.

Original language	English
Title of host publication	Distributed Computer and Communication Networks - 27th International Conference, DCCN 2024, Revised Selected Papers
Editors	Vladimir M. Vishnevsky, Konstantin E. Samouylov, Dmitry V. Kozyrev
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	480-487
Number of pages	8
ISBN (Print)	9783031808524
DOIs	https://doi.org/10.1007/978-3-031-80853-1_36
State	Published - 2025
Event	27th International Conference on Distributed Computer and Communication Networks, DCCN 2024 - Moscow, Russian Federation Duration: 23 Sep 2024 → 27 Sep 2024

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	15460 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	27th International Conference on Distributed Computer and Communication Networks, DCCN 2024
Country/Territory	Russian Federation
City	Moscow
Period	23/09/24 → 27/09/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

Blockchain
Consensus
Distributed algorithm
Energy
Storage

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-031-80853-1_36

Cite this

Kara, M., Laouid, A., Hammoudeh, M., Makeeva, E., & Bounceur, A. (2025). A New Mining Consensus Algorithm: A Binary Matrix Representation Based. In V. M. Vishnevsky, K. E. Samouylov, & D. V. Kozyrev (Eds.), Distributed Computer and Communication Networks - 27th International Conference, DCCN 2024, Revised Selected Papers (pp. 480-487). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 15460 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-80853-1_36

Kara, Mostefa ; Laouid, Abdelkader ; Hammoudeh, Mohammad et al. / A New Mining Consensus Algorithm : A Binary Matrix Representation Based. Distributed Computer and Communication Networks - 27th International Conference, DCCN 2024, Revised Selected Papers. editor / Vladimir M. Vishnevsky ; Konstantin E. Samouylov ; Dmitry V. Kozyrev. Springer Science and Business Media Deutschland GmbH, 2025. pp. 480-487 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{cc77a08779b245e585be1ea496d12051,

title = "A New Mining Consensus Algorithm: A Binary Matrix Representation Based",

abstract = "Abdelkader et al. recently proposed a new data representation method designed to enable efficient storage and management of diverse data types on the blockchain, guarantee scalability, cost-effectiveness, and network efficiency. They transformed a binary matrix M of dimensions m×n bits into two vectors H and V with sizes m′ and n′, respectively. The compression rate given by (m′+n′+∣Hash(M)∣)×100(m×n) expands exponentially, i.e., 2λ with λ depends on m and n), making their technique highly effective for data size reduction. For instance, with a matrix M of size 512×512 bits, they achieved a reduction rate of 96.42\%. The conversion from M to (H, V) is both fast and simple. The presented paper uses these parameters to create a new consensus algorithm based on solving the challenge of recovering the original data using H, V, and Hash(M) in order to determine the next miner.",

keywords = "Blockchain, Consensus, Distributed algorithm, Energy, Storage",

author = "Mostefa Kara and Abdelkader Laouid and Mohammad Hammoudeh and Elena Makeeva and Ahcene Bounceur",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 27th International Conference on Distributed Computer and Communication Networks, DCCN 2024 ; Conference date: 23-09-2024 Through 27-09-2024",

year = "2025",

doi = "10.1007/978-3-031-80853-1\_36",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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editor = "Vishnevsky, \{Vladimir M.\} and Samouylov, \{Konstantin E.\} and Kozyrev, \{Dmitry V.\}",

booktitle = "Distributed Computer and Communication Networks - 27th International Conference, DCCN 2024, Revised Selected Papers",

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Kara, M, Laouid, A, Hammoudeh, M, Makeeva, E & Bounceur, A 2025, A New Mining Consensus Algorithm: A Binary Matrix Representation Based. in VM Vishnevsky, KE Samouylov & DV Kozyrev (eds), Distributed Computer and Communication Networks - 27th International Conference, DCCN 2024, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 15460 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 480-487, 27th International Conference on Distributed Computer and Communication Networks, DCCN 2024, Moscow, Russian Federation, 23/09/24. https://doi.org/10.1007/978-3-031-80853-1_36

A New Mining Consensus Algorithm: A Binary Matrix Representation Based. / Kara, Mostefa; Laouid, Abdelkader; Hammoudeh, Mohammad et al.
Distributed Computer and Communication Networks - 27th International Conference, DCCN 2024, Revised Selected Papers. ed. / Vladimir M. Vishnevsky; Konstantin E. Samouylov; Dmitry V. Kozyrev. Springer Science and Business Media Deutschland GmbH, 2025. p. 480-487 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 15460 LNCS).

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

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AU - Kara, Mostefa

AU - Laouid, Abdelkader

AU - Hammoudeh, Mohammad

AU - Makeeva, Elena

AU - Bounceur, Ahcene

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

PY - 2025

Y1 - 2025

N2 - Abdelkader et al. recently proposed a new data representation method designed to enable efficient storage and management of diverse data types on the blockchain, guarantee scalability, cost-effectiveness, and network efficiency. They transformed a binary matrix M of dimensions m×n bits into two vectors H and V with sizes m′ and n′, respectively. The compression rate given by (m′+n′+∣Hash(M)∣)×100(m×n) expands exponentially, i.e., 2λ with λ depends on m and n), making their technique highly effective for data size reduction. For instance, with a matrix M of size 512×512 bits, they achieved a reduction rate of 96.42%. The conversion from M to (H, V) is both fast and simple. The presented paper uses these parameters to create a new consensus algorithm based on solving the challenge of recovering the original data using H, V, and Hash(M) in order to determine the next miner.

AB - Abdelkader et al. recently proposed a new data representation method designed to enable efficient storage and management of diverse data types on the blockchain, guarantee scalability, cost-effectiveness, and network efficiency. They transformed a binary matrix M of dimensions m×n bits into two vectors H and V with sizes m′ and n′, respectively. The compression rate given by (m′+n′+∣Hash(M)∣)×100(m×n) expands exponentially, i.e., 2λ with λ depends on m and n), making their technique highly effective for data size reduction. For instance, with a matrix M of size 512×512 bits, they achieved a reduction rate of 96.42%. The conversion from M to (H, V) is both fast and simple. The presented paper uses these parameters to create a new consensus algorithm based on solving the challenge of recovering the original data using H, V, and Hash(M) in order to determine the next miner.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Kara M, Laouid A, Hammoudeh M, Makeeva E, Bounceur A. A New Mining Consensus Algorithm: A Binary Matrix Representation Based. In Vishnevsky VM, Samouylov KE, Kozyrev DV, editors, Distributed Computer and Communication Networks - 27th International Conference, DCCN 2024, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2025. p. 480-487. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-80853-1_36

A New Mining Consensus Algorithm: A Binary Matrix Representation Based

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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