Tasks scheduling in distributed fog layer and cloud computing systems using dung beetle optimization algorithm
Subject Areas : information technology
mohsen eghbali
1
(Department of Computer Engineering, Maybod Branch, Islamic Azad University, Maybod, Iran)
reza aziz
2
(Associate Professor, Department of Computer Engineering, Maybod Branch, Islamic Azad University, Maybod, Iran)
Keywords: Cloud layer, Dung beetle optimization algorithm, Fog layer, Task scheduling, Internet of Things,
Abstract :
The Internet of Things has grown significantly in the past few years, and many intelligent objects have been connected to it. Cloud computing is a data processing system in the Internet of Things. However, the servers in the cloud computing paradigm are usually located at a long physical distance from the Internet of Things devices. The high latency caused by long distances cannot effectively implement real-time Internet of Things applications. Edge and fog computing has emerged as a popular computing technology in the field of the Internet of Things. One of the critical challenges of the Internet of Things is the problem of scheduling tasks in the fog and cloud layer. In the proposed method, the LSTM neural network allocates free resources, and the dung beetle optimization algorithm is used to schedule tasks optimally in the cloud and fog layer. Experiments show that in the HPC2N data set, the accuracy, sensitivity, and precision of the proposed method for predicting the state of resources are equal to 94.72%, 93.21%, and 91.64%, respectively. In the NASA data set, the proposed method's accuracy, sensitivity, and precision in resource allocation are 95.68%, 94.61%, and 92.37%, respectively. The proposed method is more accurate in allocating resources for scheduling than the RNN, 1DCNN, and MLP methods. The Makespan index of the proposed method shows a lower and better value in task scheduling than the AO_AVOA, AVOA, PSO, HHO, and FA methods.
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