Abstract
Cloud computing usually needs to process a large number of computing tasks, and task scheduling strategies play a key role in determining the efficiency of cloud computing. How to allocate computing resources reasonably and schedule task operations effectively so that the time and cost required to complete all tasks are shorter is an important issue. This paper proposes an Improved Genetic Algorithm (I-GA) that considers time and cost constraints. The result of scheduling by this algorithm can not only make the task completion time shorter, but also cost less. Through experiments, I-GA is compared with Genetic Algorithm (T-GA) considering time constraints and Genetic Algorithm (C-GA) considering cost constraints. The experimental results show that this algorithm is an effective task scheduling algorithm in cloud computing.
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Pabboju, S.S., Adilakshmi, T. (2021). Task Scheduling in Cloud Using Improved Genetic Algorithm. In: Satapathy, S.C., Bhateja, V., Favorskaya, M.N., Adilakshmi, T. (eds) Smart Computing Techniques and Applications. Smart Innovation, Systems and Technologies, vol 224. Springer, Singapore. https://doi.org/10.1007/978-981-16-1502-3_25
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DOI: https://doi.org/10.1007/978-981-16-1502-3_25
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