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Abstract This paper aims to improve the overall task processing time of mobile real-time Internet of Things (IoT) applications in fog-cloud computing, considering the various resource and security requirements along with the time constraints of the task. Fog computing extends the cloud resources to serve the IoT devices at the network edge. In such a scenario, deciding whether the tasks should be processed at the fog layer or submitted to the cloud is critical. Moreover, for real-time applications, the mobility of IoT devices and the limited bandwidth available at the edge devices endanger the low processing time of the task. Besides, the security demands of some IoT applications (i.e. healthcare) require processing the tasks by specific fog or cloud servers to assure confidentiality of information, which may also delay the task processing time. Therefore, we first address the mobility issue by proposing three different algorithms that work on allocating the mobile IoT device to the appropriate edge device (i.e. fog gateway), considering the distance and bandwidth load factors. Then, we offer a novel task scheduling algorithm that uses fuzzy logic to optimize the distribution of tasks between the fog and cloud layers, considering the task security requirements. The algorithm selects the proper processing unit to execute the task in the fog layer by exploiting the task demands (i.e. computation, storage, bandwidth, security) and deadline. Results demonstrate that considering the factors of distance and available bandwidth load while allocating the IoT device to the fog gateway improves the task processing time better than adopting one aspect. Results also show that our proposed scheduling algorithm outperforms other existing algorithms regarding makespan, turnaround time, success ratio and processing time metrics.
Ali et al. (Wed,) studied this question.