Fog-cloud task scheduling of energy consumption optimisation with deadline consideration

Jiuyun Xu, Xiaoting Sun, Ruru Zhang, Hongliang Liang, Qiang Duan

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)375-392
Number of pages18
JournalInternational Journal of Internet Manufacturing and Services
Issue number4
StatePublished - 2020

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Industrial and Manufacturing Engineering
  • Information Systems and Management


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