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Madni, S. H. H., Abd Latiff, M. S., & Coulibaly, Y. (2016). Resource scheduling for infrastructure as a service (IaaS) in cloud computing: Challenges and opportunities. Journal of Network and Computer Applications, 68, 173-200.MadniS. H. H.Abd LatiffM. S. & CoulibalyY. (2016). Resource scheduling for infrastructure as a service (IaaS) in cloud computing: Challenges and opportunities. Journal of Network and Computer Applications, 68, 173-200.Search in Google Scholar
Kumar, M., Sharma, S. C., Goel, A., & Singh, S. P. (2019). A comprehensive survey for scheduling techniques in cloud computing. Journal of Network and Computer Applications, 143, 1-33.KumarM.SharmaS. C.GoelA. & SinghS. P. (2019). A comprehensive survey for scheduling techniques in cloud computing. Journal of Network and Computer Applications, 143, 1-33.Search in Google Scholar
Wang, X., Wang, K., Wu, S., Di, S., Yang, K., & Jin, H. (2016, June). Dynamic resource scheduling in cloud radio access network with mobile cloud computing. In 2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS) (pp. 1-6). IEEE.WangX.WangK.WuS.DiS.YangK. & JinH. (2016, June). Dynamic resource scheduling in cloud radio access network with mobile cloud computing. In 2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS) (pp. 1-6). IEEE.Search in Google Scholar
Zhou, G., Tian, W., Buyya, R., Xue, R., & Song, L. (2024). Deep reinforcement learning-based methods for resource scheduling in cloud computing: A review and future directions. Artificial Intelligence Review, 57(5), 124.ZhouG.TianW.BuyyaR.XueR. & SongL. (2024). Deep reinforcement learning-based methods for resource scheduling in cloud computing: A review and future directions. Artificial Intelligence Review, 57(5), 124.Search in Google Scholar
Bölöni, L., & Turgut, D. (2017). Value of information based scheduling of cloud computing resources. Future Generation Computer Systems, 71, 212-220.BölöniL. & TurgutD. (2017). Value of information based scheduling of cloud computing resources. Future Generation Computer Systems, 71, 212-220.Search in Google Scholar
Khallouli, W., & Huang, J. (2022). Cluster resource scheduling in cloud computing: literature review and research challenges. The Journal of supercomputing, 78(5), 6898-6943.KhallouliW. & HuangJ. (2022). Cluster resource scheduling in cloud computing: literature review and research challenges. The Journal of supercomputing, 78(5), 6898-6943.Search in Google Scholar
Yu, H. (2021). Evaluation of cloud computing resource scheduling based on improved optimization algorithm. Complex & Intelligent Systems, 7(4), 1817-1822.YuH. (2021). Evaluation of cloud computing resource scheduling based on improved optimization algorithm. Complex & Intelligent Systems, 7(4), 1817-1822.Search in Google Scholar
Zhang, Y., Liu, B., Gong, Y., Huang, J., Xu, J., & Wan, W. (2024, April). Application of machine learning optimization in cloud computing resource scheduling and management. In Proceedings of the 5th International Conference on Computer Information and Big Data Applications (pp. 171-175).ZhangY.LiuB.GongY.HuangJ.XuJ. & WanW. (2024, April). Application of machine learning optimization in cloud computing resource scheduling and management. In Proceedings of the 5th International Conference on Computer Information and Big Data Applications (pp. 171-175).Search in Google Scholar
Zhu, W., Zhuang, Y., & Zhang, L. (2017). A three-dimensional virtual resource scheduling method for energy saving in cloud computing. Future Generation Computer Systems, 69, 66-74.ZhuW.ZhuangY. & ZhangL. (2017). A three-dimensional virtual resource scheduling method for energy saving in cloud computing. Future Generation Computer Systems, 69, 66-74.Search in Google Scholar
Priya, V., Kumar, C. S., & Kannan, R. (2019). Resource scheduling algorithm with load balancing for cloud service provisioning. Applied Soft Computing, 76, 416-424.PriyaV.KumarC. S. & KannanR. (2019). Resource scheduling algorithm with load balancing for cloud service provisioning. Applied Soft Computing, 76, 416-424.Search in Google Scholar
Mehta, H., Prasad, V. K., & Bhavsar, M. (2017). Efficient resource scheduling in cloud computing. International Journal of Advanced Research in Computer Science, 8(3), 809-815.MehtaH.PrasadV. K. & BhavsarM. (2017). Efficient resource scheduling in cloud computing. International Journal of Advanced Research in Computer Science, 8(3), 809-815.Search in Google Scholar
Eswaraprasad, R., & Raja, L. (2017). A review of virtual machine (VM) resource scheduling algorithms in cloud computing environment. Journal of Statistics and Management Systems, 20(4), 703-711.EswaraprasadR. & RajaL. (2017). A review of virtual machine (VM) resource scheduling algorithms in cloud computing environment. Journal of Statistics and Management Systems, 20(4), 703-711.Search in Google Scholar
Lin, W., Xu, S., He, L., & Li, J. (2017). Multi-resource scheduling and power simulation for cloud computing. Information Sciences, 397, 168-186.LinW.XuS.HeL. & LiJ. (2017). Multi-resource scheduling and power simulation for cloud computing. Information Sciences, 397, 168-186.Search in Google Scholar
Muthu, A. B. A., & Enoch, S. (2017). Optimized scheduling and resource allocation using evolutionary algorithms in cloud environment. International Journal of Intelligent Engineering and Systems, 10(5), 125-133.MuthuA. B. A. & EnochS. (2017). Optimized scheduling and resource allocation using evolutionary algorithms in cloud environment. International Journal of Intelligent Engineering and Systems, 10(5), 125-133.Search in Google Scholar
Liu, S., & Wang, N. (2020). Collaborative optimization scheduling of cloud service resources based on improved genetic algorithm. IEEE Access, 8, 150878-150890.LiuS. & WangN. (2020). Collaborative optimization scheduling of cloud service resources based on improved genetic algorithm. IEEE Access, 8, 150878-150890.Search in Google Scholar
Devarasetty, P., & Reddy, S. (2021). Genetic algorithm for quality of service based resource allocation in cloud computing. Evolutionary Intelligence, 14, 381-387.DevarasettyP. & ReddyS. (2021). Genetic algorithm for quality of service based resource allocation in cloud computing. Evolutionary Intelligence, 14, 381-387.Search in Google Scholar
Zhou, G., Tian, W., Buyya, R., & Wu, K. (2023). Growable Genetic Algorithm with Heuristic-based Local Search for multi-dimensional resources scheduling of cloud computing. Applied Soft Computing, 136, 110027.ZhouG.TianW.BuyyaR. & WuK. (2023). Growable Genetic Algorithm with Heuristic-based Local Search for multi-dimensional resources scheduling of cloud computing. Applied Soft Computing, 136, 110027.Search in Google Scholar
Fu, X., Sun, Y., Wang, H., & Li, H. (2023). Task scheduling of cloud computing based on hybrid particle swarm algorithm and genetic algorithm. Cluster Computing, 26(5), 2479-2488.FuX.SunY.WangH. & LiH. (2023). Task scheduling of cloud computing based on hybrid particle swarm algorithm and genetic algorithm. Cluster Computing, 26(5), 2479-2488.Search in Google Scholar
Ramasubbareddy, S., Swetha, E., Luhach, A. K., & Srinivas, T. A. S. (2021). A multi-objective genetic algorithm-based resource scheduling in mobile cloud computing. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 15(3), 58-73.RamasubbareddyS.SwethaE.LuhachA. K. & SrinivasT. A. S. (2021). A multi-objective genetic algorithm-based resource scheduling in mobile cloud computing. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 15(3), 58-73.Search in Google Scholar
Pirozmand, P., Hosseinabadi, A. A. R., Farrokhzad, M., Sadeghilalimi, M., Mirkamali, S., & Slowik, A. (2021). Multi-objective hybrid genetic algorithm for task scheduling problem in cloud computing. Neural computing and applications, 33, 13075-13088.PirozmandP.HosseinabadiA. A. R.FarrokhzadM.SadeghilalimiM.MirkamaliS. & SlowikA. (2021). Multi-objective hybrid genetic algorithm for task scheduling problem in cloud computing. Neural computing and applications, 33, 13075-13088.Search in Google Scholar
Shi, F. (2024). A genetic algorithm‐based virtual machine scheduling algorithm for energy‐efficient resource management in cloud computing. Concurrency and Computation: Practice and Experience, 36(22), e8207.ShiF. (2024). A genetic algorithm‐based virtual machine scheduling algorithm for energy‐efficient resource management in cloud computing. Concurrency and Computation: Practice and Experience, 36(22), e8207.Search in Google Scholar
Hamed, A. Y., & Alkinani, M. H. (2021). Task scheduling optimization in cloud computing based on genetic algorithms. Comput. Mater. Contin, 69(03), 3289-3301.HamedA. Y. & AlkinaniM. H. (2021). Task scheduling optimization in cloud computing based on genetic algorithms. Comput. Mater. Contin, 69(03), 3289-3301.Search in Google Scholar
Yin, S., Ke, P., & Tao, L. (2018, May). An improved genetic algorithm for task scheduling in cloud computing. In 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA) (pp. 526-530). IEEE.YinS.KeP. & TaoL. (2018, May). An improved genetic algorithm for task scheduling in cloud computing. In 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA) (pp. 526-530). IEEE.Search in Google Scholar
Gupta, I., Kumar, M. S., & Jana, P. K. (2018). Efficient workflow scheduling algorithm for cloud computing system: a dynamic priority-based approach. Arabian Journal for Science and Engineering, 43(12), 7945-7960.GuptaI.KumarM. S. & JanaP. K. (2018). Efficient workflow scheduling algorithm for cloud computing system: a dynamic priority-based approach. Arabian Journal for Science and Engineering, 43(12), 7945-7960.Search in Google Scholar
Lipsa, S., Dash, R. K., Ivković, N., & Cengiz, K. (2023). Task scheduling in cloud computing: A priority-based heuristic approach. IEEE access, 11, 27111-27126.LipsaS.DashR. K.IvkovićN. & CengizK. (2023). Task scheduling in cloud computing: A priority-based heuristic approach. IEEE access, 11, 27111-27126.Search in Google Scholar
Ben Alla, H., Ben Alla, S., Ezzati, A., & Touhafi, A. (2021). A novel multiclass priority algorithm for task scheduling in cloud computing. The Journal of Supercomputing, 77(10), 11514-11555.Ben AllaH.Ben AllaS.EzzatiA. & TouhafiA. (2021). A novel multiclass priority algorithm for task scheduling in cloud computing. The Journal of Supercomputing, 77(10), 11514-11555.Search in Google Scholar
Haque, M., Islam, R., Rubayeth Kabir, M., Narin Nur, F., & Nessa Moon, N. (2019). A priority-based process scheduling algorithm in cloud computing. In Emerging Technologies in Data Mining and Information Security: Proceedings of IEMIS 2018, Volume 1 (pp. 239-248). Springer Singapore.HaqueM.IslamR.Rubayeth KabirM.Narin NurF. & Nessa MoonN. (2019). A priority-based process scheduling algorithm in cloud computing. In Emerging Technologies in Data Mining and Information Security: Proceedings of IEMIS 2018, Volume 1 (pp. 239-248). Springer Singapore.Search in Google Scholar
Pirozmand, P., Jalalinejad, H., Hosseinabadi, A. A. R., Mirkamali, S., & Li, Y. (2023). An improved particle swarm optimization algorithm for task scheduling in cloud computing. Journal of Ambient Intelligence and Humanized Computing, 14(4), 4313-4327.PirozmandP.JalalinejadH.HosseinabadiA. A. R.MirkamaliS. & LiY. (2023). An improved particle swarm optimization algorithm for task scheduling in cloud computing. Journal of Ambient Intelligence and Humanized Computing, 14(4), 4313-4327.Search in Google Scholar
Wu, Z., & Xiong, J. (2021). A novel task-scheduling algorithm of cloud computing based on particle swarm optimization. International Journal of Gaming and Computer-Mediated Simulations (IJGCMS), 13(2), 1-15.WuZ. & XiongJ. (2021). A novel task-scheduling algorithm of cloud computing based on particle swarm optimization. International Journal of Gaming and Computer-Mediated Simulations (IJGCMS), 13(2), 1-15.Search in Google Scholar
Tang, X., Shi, C., Deng, T., Wu, Z., & Yang, L. (2021). Parallel random matrix particle swarm optimization scheduling algorithms with budget constraints on cloud computing systems. Applied Soft Computing, 113, 107914.TangX.ShiC.DengT.WuZ. & YangL. (2021). Parallel random matrix particle swarm optimization scheduling algorithms with budget constraints on cloud computing systems. Applied Soft Computing, 113, 107914.Search in Google Scholar
Potu, N., Jatoth, C., & Parvataneni, P. (2021). Optimizing resource scheduling based on extended particle swarm optimization in fog computing environments. Concurrency and Computation: Practice and Experience, 33(23), e6163.PotuN.JatothC. & ParvataneniP. (2021). Optimizing resource scheduling based on extended particle swarm optimization in fog computing environments. Concurrency and Computation: Practice and Experience, 33(23), e6163.Search in Google Scholar
Mengqiu Lu. (2025). Hybrid manufacturing thermal cost testing and enterprise financial optimization based on artificial intelligence and cloud computing. Thermal Science and Engineering Progress103117-103117.LuMengqiu. (2025). Hybrid manufacturing thermal cost testing and enterprise financial optimization based on artificial intelligence and cloud computing. Thermal Science and Engineering Progress103117-103117.Search in Google Scholar
Prashant Shukla & Sudhakar Pandey. (2024). MOTORS: multi-objective task offloading and resource scheduling algorithm for heterogeneous fog-cloud computing scenario. The Journal of Supercomputing (15), 22315-22361.ShuklaPrashant & PandeySudhakar. (2024). MOTORS: multi-objective task offloading and resource scheduling algorithm for heterogeneous fog-cloud computing scenario. The Journal of Supercomputing (15), 22315-22361.Search in Google Scholar
Jungwoog Kim,Minsoo Choi,Wongwan Jung & Daejun Chang. (2025). Investigation of combined process characteristics in hydrogen production and liquefaction by PEM electrolyzer and Claude cycle with liquid nitrogen precooling under varying pressure using genetic algorithm. Energy Conversion and Management119368-119368.KimJungwoogChoiMinsooJungWongwan & ChangDaejun. (2025). Investigation of combined process characteristics in hydrogen production and liquefaction by PEM electrolyzer and Claude cycle with liquid nitrogen precooling under varying pressure using genetic algorithm. Energy Conversion and Management119368-119368.Search in Google Scholar
Gundreddi Deepika Reddy,Nageswara Rao Medikondu,T. Vijaya Kumar,Sireesha Koneru,Phaneendra Babu Bobba,Atul Singla... & Hassan M. Al Jawahry. (2024). Intelligent optimization for multiprocessor systems: hybrid algorithmic strategies for scheduling and load balancing. Cogent Engineering(1).ReddyGundreddi DeepikaMedikonduNageswara RaoVijaya KumarT.KoneruSireeshaBobbaPhaneendra BabuSinglaAtul... & Al JawahryHassan M.. (2024). Intelligent optimization for multiprocessor systems: hybrid algorithmic strategies for scheduling and load balancing. Cogent Engineering(1).Search in Google Scholar
Bouhouch Laila,Zbakh Mostapha & Tadonki Claude. (2024). DFMCloudsim: an extension of cloudsim for modeling and simulation of data fragments migration over distributed data centers. International Journal of Computers and Applications(1),1-20.LailaBouhouchMostaphaZbakh & ClaudeTadonki. (2024). DFMCloudsim: an extension of cloudsim for modeling and simulation of data fragments migration over distributed data centers. International Journal of Computers and Applications(1),1-20.Search in Google Scholar