Cloud–Fog–Based Smart Grid Model for Efficient Resource Management

Saman Zahoor, Sakeena Javaid, Nadeem Javaid, Mahmood Ashraf, Farruh Ishmanov and Muhammad Khalil Afzal
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Saman Zahoor: Department of Computer Science, COMSATS University, Islamabad 44000, Pakistan
Sakeena Javaid: Department of Computer Science, COMSATS University, Islamabad 44000, Pakistan
Nadeem Javaid: Department of Computer Science, COMSATS University, Islamabad 44000, Pakistan
Mahmood Ashraf: Department of Computer Science, Federal Urdu University of Arts, Science and Technology, Islamabad 44000, Pakistan
Farruh Ishmanov: Department of Electronics and Communication Engineering, Kwangwoon University, Seoul 01897, Korea
Muhammad Khalil Afzal: Department of Computer Science, COMSATS Institute of Information Technology, Wah Cantonment 47040, Pakistan

Sustainability, 2018, vol. 10, issue 6, 1-21

Abstract: A smart grid (SG) is a modernized electric grid that enhances the reliability, efficiency, sustainability, and economics of electricity services. Moreover, it plays a vital role in modern energy infrastructure. The core challenge faced by SGs is how to efficiently utilize different kinds of front-end smart devices, such as smart meters and power assets, and in what manner to process the enormous volume of data received from these devices. Furthermore, cloud and fog computing provide on-demand resources for computation, which is a good solution to overcome SG hurdles. Fog-based cloud computing has numerous good characteristics, such as cost-saving, energy-saving, scalability, flexibility, and agility. Resource management is one of the big issues in SGs. In this paper, we propose a cloud–fog–based model for resource management in SGs. The key idea of the proposed work is to determine a hierarchical structure of cloud–fog computing to provide different types of computing services for SG resource management. Regarding the performance enhancement of cloud computing, different load balancing techniques are used. For load balancing between an SG user’s requests and service providers, five algorithms are implemented: round robin, throttled, artificial bee colony (ABC), ant colony optimization (ACO), and particle swarm optimization. Moreover, we propose a hybrid approach of ACO and ABC known as hybrid artificial bee ant colony optimization (HABACO). Simulation results show that our proposed technique HABACO outperformed the other techniques.

Keywords: cloud computing; smart grid; fog; resource management; smart devices; load balancing (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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