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01.07.2022

FPSO-GA: A Fuzzy Metaheuristic Load Balancing Algorithm to Reduce Energy Consumption in Cloud Networks

verfasst von: Seyedeh Maedeh Mirmohseni, Chunming Tang, Amir Javadpour

Erschienen in: Wireless Personal Communications

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Abstract

Load balancing in the cloud is a strategy that assures that the overall performance of large-scale computing systems can be improved by ensuring a uniform allocation of local workloads among computing system components. Many studies and algorithms in cloud computing load balancing, task scheduling, and workflow scheduling have been proposed so far. However, because of the enormous number of competing criteria and the different nature of dynamic Task allocation to heterogeneous resources that deal with scheduling, it is nearly difficult to identify an optimal solution for every scheduling problem at any given time. One of the scheduling ways is to apply meta-heuristic techniques, which attempt to discover a near-optimal solution in a predictable amount of time while demonstrating exceptional performance on the goal task. We develop a hybrid Fuzzy Particle Swarm Optimization Genetic Algorithm (FPSO-GA) method that combines a fuzzy particle swarm optimization method and a genetic algorithm in this study.
Literatur
12.
Zurück zum Zitat B. Shankar and P. Mishra, Cloud Computing for Optimization: Foundations, Applications, and Challenges. 2018. B. Shankar and P. Mishra, Cloud Computing for Optimization: Foundations, Applications, and Challenges. 2018.
20.
Zurück zum Zitat Kanani, B., & Maniyar, B. (2015). Review on max-min task scheduling algorithm for cloud computing. Journal of Emerging Technologies and Innovative Research, 2(3), 781–784. Kanani, B., & Maniyar, B. (2015). Review on max-min task scheduling algorithm for cloud computing. Journal of Emerging Technologies and Innovative Research, 2(3), 781–784.
32.
Zurück zum Zitat “2021-Optimizing bag-of-tasks scheduling on cloud data centers.pdf.” “2021-Optimizing bag-of-tasks scheduling on cloud data centers.pdf.”
33.
Zurück zum Zitat Tarawneh, H., Alhadid, I., Khwaldeh, S., and Afaneh, S. (2022). “SS symmetry an intelligent cloud service composition optimization using”. Tarawneh, H., Alhadid, I., Khwaldeh, S., and Afaneh, S. (2022). “SS symmetry an intelligent cloud service composition optimization using”.
35.
Zurück zum Zitat Javadpour, A., Adelpour, N., Wang, G., and Peng, T. (2018). “Combing Fuzzy Clustering and PSO Algorithms to Optimize Energy Consumption in WSN Networks,” 2018 IEEE Smart World, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), pp. 1371–1377 Javadpour, A., Adelpour, N., Wang, G., and Peng, T. (2018). “Combing Fuzzy Clustering and PSO Algorithms to Optimize Energy Consumption in WSN Networks,” 2018 IEEE Smart World, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), pp. 1371–1377
37.
Zurück zum Zitat Sun, C. C. (2010). A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods. Expert Systems with Applications, 37(12), 7745–7754. CrossRef Sun, C. C. (2010). A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods. Expert Systems with Applications, 37(12), 7745–7754. CrossRef
Metadaten
Titel
FPSO-GA: A Fuzzy Metaheuristic Load Balancing Algorithm to Reduce Energy Consumption in Cloud Networks
verfasst von
Seyedeh Maedeh Mirmohseni
Chunming Tang
Amir Javadpour
Publikationsdatum
01.07.2022
Verlag
Springer US
Erschienen in
Wireless Personal Communications
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-022-09897-3