Abstract
Cloud is a new concept in Internet technology and has brought many benefits, particularly, in the field of computing. Cloud has changed how on-demand resources are allocated to the different user requests and has provided more optimal resource utilization. Tasks (user requests) have different kinds, including deadline-based tasks having time-related limitations. This kind of task has various parameters and scheduling them is more challenging than scheduling the individual tasks. In this regard, many papers have been published according to these parameters. The objective of this paper is to propose a novel self-adaptive hybrid ICA–PSO algorithm for dealing with associate multi-task scheduling problem. To improve the exploration, two algorithms, namely, the imperialist competitive algorithm (ICA) and particle swarm optimization (PSO) were combined in this study. The results of the present study outperform those of the existing mechanisms.
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Tabrizchi, H., Kuchaki Rafsanjani, M., Balas, V.E. (2021). Multi-task Scheduling Algorithm Based on Self-adaptive Hybrid ICA–PSO Algorithm in Cloud Environment. In: Balas, V., Jain, L., Balas, M., Shahbazova, S. (eds) Soft Computing Applications. SOFA 2018. Advances in Intelligent Systems and Computing, vol 1222. Springer, Cham. https://doi.org/10.1007/978-3-030-52190-5_30
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DOI: https://doi.org/10.1007/978-3-030-52190-5_30
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