The week's pick
Reseach Article
Performance Analysis of Multitask Scheduling in Cloud Computing System using Whale Optimization-based Algorithms: A Survey
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 186 - Number 35 |
| Year of Publication: 2024 |
| Authors: S. Kavitha, G. Paramasivam |
10.5120/ijca2024923909
|
S. Kavitha, G. Paramasivam . Performance Analysis of Multitask Scheduling in Cloud Computing System using Whale Optimization-based Algorithms: A Survey. International Journal of Computer Applications. 186, 35 ( Aug 2024), 1-7. DOI=10.5120/ijca2024923909
Abstract
The rapid growth of cloud computing and task scheduling has become a critical aspect that significantly impacts the overall performance and productivity of cloud-based applications. For service providers and users, inadequate resource management and inefficient task scheduling can result in high cost and resource wastage. In recent years, metaheuristic algorithms have gained prominence for task scheduling in cloud environments. Among them, Whale Optimization Algorithm (WOA) can efficiently explore solution space and optimize complex objective functions. This review paper provides an extensive overview along with the application of WOA-based task scheduling methods in cloud computing. Originally, the WOA principles and operation, which highlight its salient features and optimization capabilities, were reviewed. The existing literature on WOA-based task scheduling methods is reviewed systematically and also the performance of different WOA variants is analyzed. This survey consolidates the current state-of-the-art WOA-based task scheduling methods and also offers insights into their applicability, future directions and performance. It serves as a valuable resource for researchers, practitioners, and educators seeking to understand, evaluate and advance the state-of-the-art cloud task scheduling optimization.
References
- Arunarani, A. R., Manjula, D., and Sugumaran, V. 2019. Task scheduling techniques in cloud computing: A literature survey. Future Generation Computer Systems, 91, 407-415.
- Houssein, E. H., Gad, A. G., Wazery, Y. M., and Suganthan, P. N. 2021. Task scheduling in cloud computing based on meta-heuristics: review, taxonomy, open challenges, and future trends. Swarm and Evolutionary Computation, 62, 100841.
- Mirjalili, S., and Lewis, A. 2016. The whale optimization algorithm. Advances in engineering software, 95, 51-67.
- Sreenu, K., and Sreelatha, M. 2019. W-Scheduler: whale optimization for task scheduling in cloud computing. Cluster Computing, 22, 1087-1098.
- Chen, X., Cheng, L., Liu, C., Liu, Q., Liu, J., Mao, Y., and Murphy, J. 2020. A WOA-based optimization approach for task scheduling in cloud computing systems. IEEE Systems Journal, 14(3), 3117-3128.
- Ni, L., Sun, X., Li, X., and Zhang, J. 2021. GCWOAS2: multi-objective task scheduling strategy based on Gaussian cloud-whale optimization in cloud computing. Computational Intelligence and Neuroscience, 2021, 1-17.
- Jia, L., Li, K., and Shi, X. 2021. Cloud computing task scheduling model based on improved whale optimization algorithm. Wireless Communications and Mobile Computing, 2021, 1-13.
- Ababneh, J. 2021. A hybrid approach based on grey wolf and whale optimization algorithms for solving cloud task scheduling problem. Mathematical Problems in Engineering, 2021, 1-14.
- Sanaj, M. S., and Prathap, P. J. 2021. An efficient approach to the map-reduce framework and genetic algorithm-based whale optimization algorithm for task scheduling in cloud computing environment. Materials Today: Proceedings, 37, 3199-3208.
- Manikandan, N., Gobalakrishnan, N., and Pradeep, K. 2022. Bee optimization based random double adaptive whale optimization model for task scheduling in cloud computing environment. Computer Communications, 187, 35-44.
- Chhabra, A., Sahana, S. K., Sani, N. S., Mohammadzadeh, A., and Omar, H. A. 2022. Energy-aware bag-of-tasks scheduling in the cloud computing system using hybrid oppositional differential evolution-enabled whale optimization algorithm. Energies, 15(13), 4571.
- Mangalampalli, S., Swain, S. K., and Mangalampalli, V. K. 2022. Prioritized energy efficient task scheduling algorithm in cloud computing using whale optimization algorithm. Wireless Personal Communications, 126(3), 2231-2247.
- Mangalampalli, S., Karri, G. R., and Kose, U. 2023. Multi-Objective Trust aware task scheduling algorithm in cloud computing using Whale Optimization. Journal of King Saud University-Computer and Information Sciences, 35(2), 791-809.
- Mangalampalli, S., Swain, S. K., Karri, G. R., and Mishra, S. 2023. SLA Aware Task-Scheduling Algorithm in Cloud Computing Using Whale Optimization Algorithm. Scientific Programming, 2023.
- Chakraborty, S., Saha, A. K., and Chhabra, A. 2023. Improving whale optimization algorithm with elite strategy and its application to engineering design and cloud task scheduling problems. Cognitive Computation, 1-29.
- Hosny, K. M., Awad, A. I., Khashaba, M. M., Fouda, M. M., Guizani, M., and Mohamed, E. R. 2023. Optimized multi-user dependent tasks offloading in edge-cloud computing using refined whale optimization algorithm. IEEE Transactions on Sustainable Computing.
- Khan, Z. A., Aziz, I. A., Osman, N. A. B., and Nabi, S. 2024. Parallel Enhanced Whale Optimization Algorithm for Independent Tasks Scheduling on Cloud Computing. IEEE Access.
- Gupta, S., and Singh, R. S. 2024. User-defined weight-based multi-objective task scheduling in cloud using whale optimization algorithm. Simulation Modelling Practice and Theory, 102915.
Index Terms
Keywords