Abstract:
Due to the significant communication delay to user tasks, the cloud is not ideal for executing real-time tasks with stringent
deadlines. Fog computing consists of low computation capability fog nodes, or cloudlets located in proximity to the source of the data
generation: the users. These cloudlets are ideal for executing tasks that have early deadlines. In this paper, we propose algorithms that
schedule a set of real-time tasks on such an embedded-fog-cloud architecture. We consider hard, firm and soft tasks. The execution
framework consists of embedded, fog and cloud processors. Tasks are scheduled on appropriate processors based on their deadline
requirements. In general, hard real-time tasks are executed on embedded processors, firm real-time tasks on fog processors, and soft
real-time tasks on cloud processors. We also propose a sufficient schedulability condition. Simulation results from the CERIT trace as
well as test-bed results show that the proposed algorithms offer superior performance as compared to algorithms that do not employ
fog processors. Employing an Embedded − f og − cloud architecture offers an improvement of 62.37% for real-time Success Ratio
(SR) and 35% for Average Response Time as compared to scheduling tasks on the cloud alone.
