Game theory and evolutionary optimization approaches applied to resource allocation problems in computing environments: A survey

Shahab Shamshirband; Javad Hassannataj Joloudari; Sahar Khanjani Shirkharkolaie; Sanaz Mojrian; Fatemeh Rahmani; Seyedakbar Mostafavi; Zulkefli Mansor; Shahab Shamshirband; Javad Hassannataj Joloudari; Sahar Khanjani Shirkharkolaie; Sanaz Mojrian; Fatemeh Rahmani; Seyedakbar Mostafavi; Zulkefli Mansor

doi:10.3934/mbe.2021453

Mathematical Biosciences and Engineering

2021, Volume 18, Issue 6: 9190-9232. doi: 10.3934/mbe.2021453

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Survey Special Issues

Game theory and evolutionary optimization approaches applied to resource allocation problems in computing environments: A survey

1.
Future Technology Research Center, College of Future, National Yunlin University of Science and Technology 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan
2.
Faculty of Engineering, Department of Computer Engineering, University of Birjand, Birjand, Iran
3.
Department of Information Technology, Mazandaran University of Science and Technology, Babol, Iran
4.
Department of Computer Engineering, Yazd University, Yazd, Iran
5.
Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia

Received: 29 July 2021 Accepted: 29 September 2021 Published: 25 October 2021

Today's intelligent computing environments, including the Internet of Things (IoT), Cloud Computing (CC), Fog Computing (FC), and Edge Computing (EC), allow many organizations worldwide to optimize their resource allocation regarding the quality of service and energy consumption. Due to the acute conditions of utilizing resources by users and the real-time nature of the data, a comprehensive and integrated computing environment has not yet provided a robust and reliable capability for proper resource allocation. Although traditional resource allocation approaches in a low-capacity hardware resource system are efficient for small-scale resource providers, for a complex system in the conditions of dynamic computing resources and fierce competition in obtaining resources, they cannot develop and adaptively manage the conditions optimally. To optimize the resource allocation with minimal delay, low energy consumption, minimum computational complexity, high scalability, and better resource utilization efficiency, CC/FC/EC/IoT-based computing architectures should be designed intelligently. Therefore, the objective of this research is a comprehensive survey on resource allocation problems using computational intelligence-based evolutionary optimization and mathematical game theory approaches in different computing environments according to the latest scientific research achievements.
- resource allocation,
- Internet of things,
- cloud computing,
- fog computing,
- game theory models,
- evolutionary optimization methods
Citation: Shahab Shamshirband, Javad Hassannataj Joloudari, Sahar Khanjani Shirkharkolaie, Sanaz Mojrian, Fatemeh Rahmani, Seyedakbar Mostafavi, Zulkefli Mansor. Game theory and evolutionary optimization approaches applied to resource allocation problems in computing environments: A survey[J]. Mathematical Biosciences and Engineering, 2021, 18(6): 9190-9232. doi: 10.3934/mbe.2021453

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Abstract

Today's intelligent computing environments, including the Internet of Things (IoT), Cloud Computing (CC), Fog Computing (FC), and Edge Computing (EC), allow many organizations worldwide to optimize their resource allocation regarding the quality of service and energy consumption. Due to the acute conditions of utilizing resources by users and the real-time nature of the data, a comprehensive and integrated computing environment has not yet provided a robust and reliable capability for proper resource allocation. Although traditional resource allocation approaches in a low-capacity hardware resource system are efficient for small-scale resource providers, for a complex system in the conditions of dynamic computing resources and fierce competition in obtaining resources, they cannot develop and adaptively manage the conditions optimally. To optimize the resource allocation with minimal delay, low energy consumption, minimum computational complexity, high scalability, and better resource utilization efficiency, CC/FC/EC/IoT-based computing architectures should be designed intelligently. Therefore, the objective of this research is a comprehensive survey on resource allocation problems using computational intelligence-based evolutionary optimization and mathematical game theory approaches in different computing environments according to the latest scientific research achievements.

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