FogGrid: Leveraging Fog Computing for Enhanced Smart Grid Network
Rabindra K. Barik, Satish Kumar Gudey, Gujji Giridhar Reddy, Meenakshi, Pant, Harishchandra Dubey, Kunal Mankodiya, Vinay Kumar

TL;DR
This paper presents a Fog computing framework for smart grid networks, demonstrating its benefits in reducing power consumption and storage needs through hardware implementation on a microgrid system.
Contribution
It introduces a novel Fog computing architecture based on Intel Edison for smart grids, with hardware implementation and comparative analysis against cloud computing.
Findings
Reduced power consumption in smart grid networks
Lower storage requirements with Fog computing
Effective overlay analysis capabilities
Abstract
The present manuscript concentrates on the application of Fog computing to a Smart Grid Network that comprises of a Distribution Generation System known as a Microgrid. It addresses features and advantages of a smart grid. Two computational methods for on-demand processing based on shared information resources is discussed. Fog Computing acts as an additional layer of computational and/or communication nodes that offload the Cloud backend from multi-tasking while dealing with large amounts of data. Both Fog computing and Cloud computing hierarchical architecture is compared with respect to efficient utilization of resources. To alleviate the advantages of Fog computing, a Fog computing framework based on Intel Edison is proposed. The proposed architecture has been hardware implemented for a microgrid system. The results obtained show the efficacy of Fog Computing for smart grid network…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
