Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation

Akram Alofi; Mahmoud Bokhari; Rami Bahsoon; Robert Hendley

doi:10.1145/3449726.3459558

Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation

Akram Alofi
, Mahmoud Bokhari
, Rami Bahsoon
, Robert Hendley

Computer Science

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

Abstract

In this paper, we represent the problem of selecting miners within a blockchain-based system as a subset selection problem. We formulate the problem of minimising blockchain energy consumption as an optimisation problem with two conflicting objectives: energy consumption and trust. The proposed model is compared across different algorithms to demonstrate its performance.

Original language	English
Title of host publication	GECCO '21
Subtitle of host publication	Proceedings of the Genetic and Evolutionary Computation Conference Companion
Editors	Francisco Chicano
Place of Publication	New York
Publisher	Association for Computing Machinery (ACM)
Pages	291-292
Number of pages	2
ISBN (Electronic)	9781450383516
DOIs	https://doi.org/10.1145/3449726.3459558
Publication status	Published - 7 Jul 2021
Event	2021 Genetic and Evolutionary Computation Conference, GECCO 2021 - Virtual, Online, France Duration: 10 Jul 2021 → 14 Jul 2021

Publication series

Name	GECCO: Genetic and Evolutionary Computation Conference
Publisher	Association for Computing Machinery (ACM)

Conference

Conference	2021 Genetic and Evolutionary Computation Conference, GECCO 2021
Country/Territory	France
City	Virtual, Online
Period	10/07/21 → 14/07/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

optimisation
evolutionary algorithms
mining
blockchain

Access to Document

10.1145/3449726.3459558

Cite this

Alofi, A., Bokhari, M., Bahsoon, R., & Hendley, R. (2021). Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation. In F. Chicano (Ed.), GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 291-292). (GECCO: Genetic and Evolutionary Computation Conference). Association for Computing Machinery (ACM). https://doi.org/10.1145/3449726.3459558

Alofi, Akram ; Bokhari, Mahmoud ; Bahsoon, Rami et al. / Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation. GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion. editor / Francisco Chicano. New York : Association for Computing Machinery (ACM), 2021. pp. 291-292 (GECCO: Genetic and Evolutionary Computation Conference).

@inproceedings{b8051981c5a14049a4c535bb6651f6f3,

title = "Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation",

abstract = "In this paper, we represent the problem of selecting miners within a blockchain-based system as a subset selection problem. We formulate the problem of minimising blockchain energy consumption as an optimisation problem with two conflicting objectives: energy consumption and trust. The proposed model is compared across different algorithms to demonstrate its performance.",

keywords = "optimisation, evolutionary algorithms, mining, blockchain",

author = "Akram Alofi and Mahmoud Bokhari and Rami Bahsoon and Robert Hendley",

year = "2021",

month = jul,

day = "7",

doi = "10.1145/3449726.3459558",

language = "English",

series = "GECCO: Genetic and Evolutionary Computation Conference",

publisher = "Association for Computing Machinery (ACM)",

pages = "291--292",

editor = "Francisco Chicano",

booktitle = "GECCO '21",

address = "United States",

note = "2021 Genetic and Evolutionary Computation Conference, GECCO 2021 ; Conference date: 10-07-2021 Through 14-07-2021",

}

Alofi, A, Bokhari, M, Bahsoon, R & Hendley, R 2021, Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation. in F Chicano (ed.), GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO: Genetic and Evolutionary Computation Conference, Association for Computing Machinery (ACM), New York, pp. 291-292, 2021 Genetic and Evolutionary Computation Conference, GECCO 2021, Virtual, Online, France, 10/07/21. https://doi.org/10.1145/3449726.3459558

Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation. / Alofi, Akram; Bokhari, Mahmoud; Bahsoon, Rami et al.
GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion. ed. / Francisco Chicano. New York: Association for Computing Machinery (ACM), 2021. p. 291-292 (GECCO: Genetic and Evolutionary Computation Conference).

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

TY - GEN

T1 - Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation

AU - Alofi, Akram

AU - Bokhari, Mahmoud

AU - Bahsoon, Rami

AU - Hendley, Robert

PY - 2021/7/7

Y1 - 2021/7/7

N2 - In this paper, we represent the problem of selecting miners within a blockchain-based system as a subset selection problem. We formulate the problem of minimising blockchain energy consumption as an optimisation problem with two conflicting objectives: energy consumption and trust. The proposed model is compared across different algorithms to demonstrate its performance.

AB - In this paper, we represent the problem of selecting miners within a blockchain-based system as a subset selection problem. We formulate the problem of minimising blockchain energy consumption as an optimisation problem with two conflicting objectives: energy consumption and trust. The proposed model is compared across different algorithms to demonstrate its performance.

KW - optimisation

KW - evolutionary algorithms

KW - mining

KW - blockchain

U2 - 10.1145/3449726.3459558

DO - 10.1145/3449726.3459558

M3 - Conference contribution

T3 - GECCO: Genetic and Evolutionary Computation Conference

SP - 291

EP - 292

BT - GECCO '21

A2 - Chicano, Francisco

PB - Association for Computing Machinery (ACM)

CY - New York

T2 - 2021 Genetic and Evolutionary Computation Conference, GECCO 2021

Y2 - 10 July 2021 through 14 July 2021

ER -

Alofi A, Bokhari M, Bahsoon R , Hendley R. Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation. In Chicano F, editor, GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York: Association for Computing Machinery (ACM). 2021. p. 291-292. (GECCO: Genetic and Evolutionary Computation Conference). doi: 10.1145/3449726.3459558

Selecting miners within blockchain-based systems using evolutionary algorithms for energy optimisation

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this