Abstract:
The cloud is unsuitable for real-time tasks with tight deadlines due to the communication delay to user tasks. Fog computing uses low-computing fog nodes, or cloudlets, near users to generate data. These cloudlets are ideal for early-deadline tasks.
This paper proposes algorithms to schedule real-time tasks on an embedded-fog-cloud architecture. Tasks are hard, firm, or soft. The execution framework uses embedded, fog, and cloud processors. Based on deadlines, processors schedule tasks.
Hard, firm, and soft real-time tasks run on embedded, fog, and cloud processors, respectively. We also propose sufficient schedulability. The proposed algorithms outperform fog processor-free algorithms in CERIT trace simulations and test beds. An Embedded−fog−cloud architecture improves real-time Success Ratio (SR) by 62.37 percent and Average Response Time by 35 percent compared to cloud-only scheduling.
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