An intelligent technique based on jellyfish algorithm for priority-based task scheduling in IoT/Fog networks
Subject Areas : مهندسی برق و کامپیوترS. Sohrabi 1 , M. Sakhaei 2 * , M. Nassiri 3 , R. Mohammadi 4
1 - Dept. of Comp. Eng., Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
2 - Dept. of Comp. Eng., Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
3 - Dept. of Comp. Eng., Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
4 - Dept. of Comp. Eng., Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
Keywords: Internet of Thing, Fog Computing, Resource Allocation Algorithm, Simulated Annealing Algorithm, Jellyfish Algorithm,
Abstract :
Fog computing was implemented to enhance the service quality of IoT applications in cloud computing. The increase in latency and bandwidth overhead in cloud computing is a result of IoT devices transmitting large amounts of data. IoT devices are responsible for producing significant volumes of data that need to be managed, resulting in higher demands on the fog-cloud computing network and necessitating resource management in this setting. In the fog-cloud computing system, tasks of varying priorities can be dispatched for processing. Providing an appropriate scheduling strategy for tasks in the fog layer is challenging due to the multitude of tasks and resources involved. Task scheduling in fog-cloud computing systems aims to optimize task allocation and execution while considering relevant constraints. Thus, this research suggests an enhanced method using the jellyfish algorithm and genetic algorithm to minimize energy consumption and execution time while considering task priority, which is crucial in task allocation. The results of the simulation and comparison of the suggested algorithm with other algorithms in this study support the effectiveness of the proposed method in decreasing both execution time and energy usage.
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