A Multi-objective Model for Task Scheduling Optimization in Fog-Cloud Computing Environments

Document Type : Persian Original Article

Author

Department of Computer Engineering and IT, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran.

Abstract

With the advent of Internet of Things (IoT) applications, the number of processing requests has dramatically increased. In order to response to these requests, the Fog-Cloud environment has recently been introduced as a hybrid computing system. Although, the Fog-Cloud is a very promising environment for processing IoT requests, it faces many challenges. In this regard, task scheduling problem is one of the key challenges which has a significant impact on the efficiency and overall system cost. Motivated by this, in this paper, we first present a multi-objective optimization model including makespan, energy consumption and processing cost for scheduling tasks in an integrated Fog-Cloud environment. Then we propose a heuristic algorithm to efficiently solve the model. Simulation results demonstrate that our proposed algorithm significantly reduces all the aforementioned metrics and can achieve a good tradeoff between them. Specifically, the proposed algorithm improves the objective function around 98%, 43% and 32% in comparison with the random, genetic and the power of two choices algorithms, respectively.

Keywords

References

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Journal of Soft Computing and Information Technology
Volume 10, Issue 4 - Serial Number 34
Winter
January 2022
Pages 43-52

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