Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/26688
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dc.contributor.authorAlmalki, FA-
dc.contributor.authorAngelides, MC-
dc.date.accessioned2023-06-19T14:23:24Z-
dc.date.available2023-06-19T14:23:24Z-
dc.date.issued2023-06-19-
dc.identifier.citationAlmalki, F.A. and Angelides, M.C. (2023) 'A serious gaming approach for optimization of energy allocation in CubeSats', Multimedia Tools and Applications, 0 (ahead-of-print), pp. 1 - 21. doi: 10.1007/s11042-023-15795-y.en_US
dc.identifier.issn1380-7501-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/26688-
dc.descriptionData availability: All data generated or analysed during this study are included in this article.en_US
dc.description.abstractCopyright © The Author(s) 2023. Energy consumption remains an open challenge in aerial systems such as CubeSats and therefore optimization of its allocation is a top priority for maximizing operational capacity. Our research review reveals a plethora of approaches for optimization of energy allocation and all achieving varying degrees of success and not without any compromises. In this paper, we exploit the use of serious gaming in a novel energy allocation algorithm that aims at minimizing energy consumption to maximize the utilities of both CubeSats and terrestrial sensors. To demonstrate this, we use Stackelberg for serious gaming and standalone topology for CubeSat configuration. The experimental results show that the use of a Stackelberg game approach for optimization has led to reduction in the required transmission energy in sensors, an improved link performance between the CubeSat and ground sensors, and an increase in network lifetime and performance without resorting into sensor power enhancements or other external power sources. The overall average operational capacity improvement predictions range between 22 to 27% across all performance indicators of energy efficiency across RF chains of link budgets.en_US
dc.format.extent1 - 21-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoen_USen_US
dc.publisherSpringer Natureen_US
dc.rightsCopyright © The Author(s) 2023. Rights and permissions: Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectserious gamingen_US
dc.subjectoptimizationen_US
dc.subjectenergy allocationen_US
dc.subjectenergy consumptionen_US
dc.subjectCubesaten_US
dc.subjectaerial modelen_US
dc.subjectwireless connectivityen_US
dc.titleA serious gaming approach for optimization of energy allocation in CubeSatsen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1007/s11042-023-15795-y-
dc.relation.isPartOfMultimedia Tools and Applications-
pubs.publication-statusPublished online-
pubs.volume0-
dc.identifier.eissn1573-7721-
dc.rights.holderThe Author(s)-
Appears in Collections:Dept of Computer Science Research Papers

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