International Conference on Computer and Knowledge Engineering

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An optimal workflow scheduling method in cloud-fog computing using three-objective Harris-Hawks algorithm

Authors :

Ahmadreza Montazerolghaem¹ Maryam Khosravi² Fatemeh Rezaee³

1- University of Isfahan 2- university of isfahan 3- university of isfahan

Keywords :

Internet of Things،Cloud-Fog computing،Harris hawks optimization algorithm،Workflow scheduling،DVFS

Abstract :

Today, the Internet of Things (IoT) use to collect data by sensors, and store and process them. As the IoT has limited processing and computing power, we are turning to the integration of the cloud and the IoT. The cloud computing processes the large data at high speed, but sending this large data requires a lot of bandwidth. Therefore, we use fog computing, which is close to IoT devices. In this case, the delay is reduced. Both cloud and fog computing are used to increasing performance of IoT. Job scheduling of IoT workflow requests based on cloud-fog computing plays a key role in responding to these requests. Job scheduling in order to reduce makespan time, is very important in realtime system. Also, reducing the energy consumption improves the performance of the system. In this article, three-objective Harris Hawks Optimizer (HHO) scheduling algorithm is proposed in order to reduce makespan time, energy consumption and increase reliability. Also, dynamic voltage frequency scaling (DVFS) has been used to reduce the energy consumption, which reduces the frequency of the processor. Then HHO is compared with other algorithms such as Whale Optimization Algorithm (WOA), Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) and the proposed algorithm shows better performance on experimental data. The proposed method has achieved an average reliability of 83%, energy consumption of 14.95 KJ, and makespan of 272.5 seconds.

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