Energy and Quality Aware Multi-Objective Resource Allocation Algorithm in Cloud

Koné Kigninman Désiré (), Eya Dhib, Nabil Tabbane and Olivier Asseu
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Koné Kigninman Désiré: Ecole Supérieure Africaine des TIC (ESATIC), LASTIC Abidjan, Côte d’Ivoire
Eya Dhib: #x2020;University of Carthage, SUP’COM, MEDIATRON Laboratory, Tunis, Tunisia
Nabil Tabbane: #x2020;University of Carthage, SUP’COM, MEDIATRON Laboratory, Tunis, Tunisia
Olivier Asseu: #x2021;Institut Polytechnique Felix Houphouet-Boigny (INPHB), Yamoussoukro, Côte d’Ivoire

Journal of Information & Knowledge Management (JIKM), 2021, vol. 20, issue 04, 1-26

Abstract: Cloud gaming has become the new service provisioning prototype that hosts the video games in the cloud and broadcasts the interactive game streaming to the players through the Internet. Here, the cloud must use massive resources for video representation and its streaming when several simultaneous players reach a particular point. Alternatively, various players may have separate necessities on Quality-of Experience, like low delay, high-video quality, etc. The challenging task is providing better service by the fixed cloud resource. Hence, there is a necessity for an energy-aware multi-resource allocation in the cloud. This paper devises a Fractional Rider-Harmony search algorithm (Fractional Rider-HSA) for resource allocation in the cloud. The Fractional Rider-HSA combines fractional calculus, Rider Optimization algorithm (ROA), and HSA. Moreover, the fitness function, like mean opinion score (MOS), gaming experience loss, fairness, energy consumption, and network parameters, is considered to determine the optimal resource allocation. The proposed model produces the maximal MOS of 0.8961, maximal gaming experience loss (QE) of 0.998, maximal fairness of 0.9991, the minimum energy consumption of 0.3109, and minimal delay 0.2266, respectively.

Keywords: Cloud computing; fractional calculus; spark architecture; harmony search algorithm; rider optimization algorithm (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1142/S0219649221500520

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