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A Systematic Literature Review on Task Allocation and Performance Management Techniques in Cloud Data Center

Nidhika Chauhan1, Navneet Kaur2, Kamaljit Singh Saini2, Sahil Verma3, Abdulatif Alabdulatif4, Ruba Abu Khurma5,7, Maribel Garcia-Arenas6, Pedro A. Castillo6,*

1 University Institute of Computing, Chandigarh University, Punjab, 143001, India
2 Department of Computer Science and Engineering, Chandigarh University, Punjab, 143001, India
3 Department of Computer Science and Engineering, Uttaranchal University, Uttarakhand, 248007, India
4 Department of Computer Science, College of Computer Qassim University, Buraydah, 52571, Saudi Arabia
5 MEU Research Unit, Faculty of Information Technology, Middle East University, Amman, 11831, Jordan
6 Department of Computer Engineering, Automatics and Robotics, University of Granada, Granada, 18071, Spain
7 Applied Science Research Center, Applied Science Private University, Amman, 11931, Jordan

* Corresponding Author: Pedro A. Castillo. Email: email

Computer Systems Science and Engineering 2024, 48(3), 571-608. https://doi.org/10.32604/csse.2024.042690

Abstract

As cloud computing usage grows, cloud data centers play an increasingly important role. To maximize resource utilization, ensure service quality, and enhance system performance, it is crucial to allocate tasks and manage performance effectively. The purpose of this study is to provide an extensive analysis of task allocation and performance management techniques employed in cloud data centers. The aim is to systematically categorize and organize previous research by identifying the cloud computing methodologies, categories, and gaps. A literature review was conducted, which included the analysis of 463 task allocations and 480 performance management papers. The review revealed three task allocation research topics and seven performance management methods. Task allocation research areas are resource allocation, load-Balancing, and scheduling. Performance management includes monitoring and control, power and energy management, resource utilization optimization, quality of service management, fault management, virtual machine management, and network management. The study proposes new techniques to enhance cloud computing work allocation and performance management. Short-comings in each approach can guide future research. The research’s findings on cloud data center task allocation and performance management can assist academics, practitioners, and cloud service providers in optimizing their systems for dependability, cost-effectiveness, and scalability. Innovative methodologies can steer future research to fill gaps in the literature.

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Cite This Article

APA Style
Chauhan, N., Kaur, N., Saini, K.S., Verma, S., Alabdulatif, A. et al. (2024). A systematic literature review on task allocation and performance management techniques in cloud data center. Computer Systems Science and Engineering, 48(3), 571-608. https://doi.org/10.32604/csse.2024.042690
Vancouver Style
Chauhan N, Kaur N, Saini KS, Verma S, Alabdulatif A, Khurma RA, et al. A systematic literature review on task allocation and performance management techniques in cloud data center. Comput Syst Sci Eng. 2024;48(3):571-608 https://doi.org/10.32604/csse.2024.042690
IEEE Style
N. Chauhan et al., "A Systematic Literature Review on Task Allocation and Performance Management Techniques in Cloud Data Center," Comput. Syst. Sci. Eng., vol. 48, no. 3, pp. 571-608. 2024. https://doi.org/10.32604/csse.2024.042690



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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