@Article{jqc.2020.016151,
AUTHOR = {Rizwan Munir, Yifei Wei, Rahim Ullah, Iftikhar Hussain, Kaleem Arshid, Umair Tariq},
TITLE = {Big Data of Home Energy Management in Cloud Computing},
JOURNAL = {Journal of Quantum Computing},
VOLUME = {2},
YEAR = {2020},
NUMBER = {4},
PAGES = {193--202},
URL = {http://www.techscience.com/jqc/v2n4/41126},
ISSN = {2579-0145},
ABSTRACT = {A smart grid is the evolved form of the power grid with the integration of 
sensing, communication, computing, monitoring, and control technologies. These 
technologies make the power grid reliable, efficient, and economical. However, the 
smartness boosts the volume of data in the smart grid. To obligate full benefits, big 
data has attractive techniques to process and analyze smart grid data. This paper 
presents and simulates a framework to make sure the use of big data computing 
technique in the smart grid. The offered framework comprises of the following four 
layers: (i) Data source layer, (ii) Data transmission layer, (iii) Data storage and 
computing layer, and (iv) Data analysis layer. As a proof of concept, the framework 
is simulated by taking the dataset of three cities of the Pakistan region and by 
considering two cloud-based data centers. The results are analyzed by taking into 
account the following parameters: (i) Heavy load data center, (ii) The impact of peak 
hour, (iii) High network delay, and (iv) The low network delay. The presented 
framework may help the power grid to achieve reliability, sustainability, and costefficiency for both the users and service providers.},
DOI = {10.32604/jqc.2020.016151}
}