An Efficient Data Transmission in Smart Grids Using Edge Computing

Samson Hansen Sackey, Joseph Henry Anajemba, Samuel Nartey Kofie, Godwin Kobby Gakpo


In the world of smart grids, there has been improvements like protection, efficiency and environmental friendly power systems. With a huge amount of data transmitted through the IOT devices, cloud-only architecture could not hold the delay, throughput and response time of these data via the network. For that reason, the reference architecture with the involvement of the edge computing for smart grid is established. We considered discussing edge computing as an extension of the cloud, assisting the smart meters and IoT devices in smooth data transmission to and fro the entire smart grid. The edge nodes helps to ease load on cloud, improve its performance and efficiency, and also provide real-time calculating service. Performance relating to delay, throughput and response time of cloud services and edge services is shown and evaluated. Our simulation proved that the edge based smart grid architecture has a great improvement over the cloud state of the art technique.


Smart grid, Response time, Delay, Throughput, Edge computing

Full Text:



Y. Y. Sun, J. J. Yuan, and M. Y. Zhai, “Cloud-Based Data Analysis of User Side in Smart Grid”, 2nd International Conference on Open and Big Data (OBD), pg. 39-44, 2016.

A. Sanchez, W. Rivera, ”Big Data Analysis and Visualization for the Smart Grid” International Congress on Big Data (Big Data Congress) Pages: 414 – 418, 2017.

B. E. Bilgin, S. Baktir, V. C. Gungor, “Collecting smart meter data via public transportation buses” IET Intelligent Transport Systems, Volume: 10, Issue: 8, Pages: 515 – 523, 2016.

D. Niyato, P. Wang, “Cooperative transmission for meter data collection in smart grid”, Communications Magazine, Volume: 50, Issue: 4, Pages: 90 – 97, 2012. [5] B. R. Stojkoska, K. Trivodaliev, “Enabling internet of things for smart homes through fog computing” 25th Telecommunication Forum (TELFOR), Pages: 1 – 4, 2017. [6] T. Islam, M. M. A. Hashem, “A big data management system for providing real time services using fog infrastructure” IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), Pages: 85 – 89, 2018. [7] Y. Zhang, K. Liang, S. Zhang, Y. He, “Applications of edge computing in PIoT” 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2), Year: 2017, Pages: 1 – 4.

J. Xu, B. Palanisamy, H. Ludwig, Q. Wang, “Zenith: Utility-Aware Resource Allocation for Edge Computing” IEEE International Conference on Edge Computing(EDGE), Pages: 47 – 54, 2017. [9] I. Farah Siddiqui ; Scott Uk-Jin Lee ; Asad Abbas ; Ali Kashif Bashir

Optimizing Lifespan and Energy Consumption by Smart Meters in Green-Cloud-Based Smart Grids Vol 5 Pages: 20934 – 20945, 2017. [10] N. Kumar, S. Zeadally, Joel J.P.C. Rodrigues, Vehicular delay-tolerant networks for smart grid data management using mobile edge computing” IEEE Communications Magazine, Volume: 54, Issue: 10, Pages: 60 – 66, 2016. [11] T. Islam, M. M. A. Hashem, “A big data management system for providing real time services using fog infrastructure”, IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), Pages: 85 – 89, 2018. [12] E. Oyekanlu, C. Nelatury, A. O. Fatade, O. Alaba, O. Abass, ”Edge computing for industrial IoT and the smart grid: Channel capacity for M2M communication over the power line, IEEE 3rd International Conference on Electro-Technology for National Development (NIGERCON) Pages: 1 – 11, 2017. [13] D. Bakken, A. Ackerman, A. Srivastava, P. Panciatici, M. Seewald, F. Columbus, S. Jiang, "Towards enhanced power grid management via more dynamic and flexible edge computations”, IEEE Fog World Congress (FWC)Year: 2017Pages: 1 – 8, 2017. [14] H. El-Sayed, S. Sankar, M. Prasad, D. Puthal, A. Gupta ; M. Mohanty, C. T. Lin, "Edge of Things: The Big Picture on the Integration of Edge”, IoT and the Cloud in a Distributed Computing Environment IEEE Access, Volume: 6, Pages: 1706 – 1717, 2018. [15] Y. D. Chen, M. Z. Azhari, J. S. Leu, “Design and implementation of a power consumption management system for smart homeover fog-cloud computing” 3rdInternational Conference on Intelligent Green Building and Smart Grid (IGBSG), Pages: 1 – 5, 2018. [16] M. Wang, J. Wu, G. Li, J. Li, Q. Li, S. Wang, "Toward mobility support for information-centric IoV in smart city using fog computing”, International Conference on Smart Energy Grid Engineering (SEGE), Pages: 357 – 361, 2017. [17] P. Wang, X. Chen, Z. Sun, “Performance Modelling and Suitability Assessment of Data Center Based on Fog Computing", Volume: 6, Pages: 29587 – 29593, 2018. [18] F. Yildirim, S. Ozdemir, “A secure data aggregation protocol for fog computing based smart grid” IEEE 12th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG 2018), Pages: 1 – 6, 2018. [19] W. Yu, F. Liang, X. He, W. G. Hatcher, C. Lu, J. Lin, X. Yang, “A Survey on the Edge Computing for the Internet of Things", Volume: 6, Pages: 6900 – 6919, 2018. [20] S. Dey, A. Mukherjee, H. S. Paul ; A. Pal, “Challenges of Using Edge Devices in IoT Computation”, International Conference on Parallel and Distributed Systems, Pages: 564 – 569, 2013.

T. P. Raptis, A. Passarell, M. Conti, “Performance Analysis of Latency-Aware Data Management in Industrial IoT Networks’’ Sensors 2018, 18, 2611; doi: 10.3390/s18082611,, 2018.


  • There are currently no refbacks.

Copyright (c) 2019 Samson Hansen Sackey

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.