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- Publisher
- Inderscience Publishers
- Copyright
- Copyright © Inderscience Enterprises Ltd
- ISSN
- 1751-6048
- eISSN
- 1751-6056
- DOI
- 10.1504/IJIMS.2020.110228
- Publisher site
- See Article on Publisher Site
Abstract
The emerging IoT introduces many new challenges that cannot be adequately addressed by the current 'cloud-only' architectures. The cooperation of the fog and cloud is considered to be a promising architecture, which efficiently handles IoT's data processing and communications requirements. However, how to schedule tasks to better adapt to IoT real-time needs and reduce the energy in the fog-cloud system is not well addressed. In this paper, we first model the energy consumption of the fog and cloud, respectively, and formulate a task scheduling problem into a constrained optimisation problem in fog-cloud computing system. Then, an efficient deadline-energy scheduling algorithm based on ant colony optimisation (DEACO) is put forward to tackle this problem, which achieves to reduce energy consumption on the condition of satisfying the task deadline. Finally, algorithms have been simulated on the extended CloudSim simulator. The experimental results have shown that our scheduling approach reduces energy more effective.
Journal
International Journal of Internet Manufacturing and Services – Inderscience Publishers
Published: Jan 1, 2020