Research Article
Electrical Big Data’s Stream Management for Efficient Energy Control
@INPROCEEDINGS{10.1007/978-3-031-34896-9_25, author={Jean Gane Sarr and Ndiouma Bame and Aliou Boly}, title={Electrical Big Data’s Stream Management for Efficient Energy Control}, proceedings={Towards new e-Infrastructure and e-Services for Developing Countries. 14th EAI International Conference, AFRICOMM 2022, Zanzibar, Tanzania, December 5-7, 2022, Proceedings}, proceedings_a={AFRICOMM}, year={2023}, month={6}, keywords={energy electrical data data stream summary big data data cube}, doi={10.1007/978-3-031-34896-9_25} }- Jean Gane Sarr
Ndiouma Bame
Aliou Boly
Year: 2023
Electrical Big Data’s Stream Management for Efficient Energy Control
AFRICOMM
Springer
DOI: 10.1007/978-3-031-34896-9_25
Abstract
Energy is crucial for any activity of a country. Therefore, electrical organizations need to analyze the data generated in the form of data streams by network equipment’s for decisions making. These data are voluminous and velocious, which make impossible to process or store them with conventional methods. Hence the need to have a tool that allows to exploit these electrical data from the user’s consumption and the network. In this paper, we propose a tool that summaries data streams by using data cubes structures and gives the ability to face the need to make the best decisions required by the customer as well as the supplier. This tool is composed by a data stream summary model and two algorithms used to create, load, and update the data cubes. This proposal was performed with Big Data tools that give to this summary the capacity to scale up. To demonstrate the effectiveness of the proposition, a detailed experimental evaluation over a real electrical data stream is presented.
