BEDS: Blockchain energy efficient IoE sensors data scheduling for smart home and vehicle applications

Abdullah Lakhan, Mazin Abed Mohammed, Karrar Hameed Abdulkareem, Muhammet Deveci, Haydar Abdulameer Marhoon, Sajida Memon, Jan Nedoma and Radek Martinek

Applied Energy, 2024, vol. 369, issue C, No S0306261924009188

Abstract: In the current period, there has been a prominent and gradual upswing in the application of Internet of Energy (IoE) sensors in smart cities. These sensors play a vital role across diverse aspects of the energy sector, ranging from producing energy to haggling with the complexities of the smart grid. The IoE sensors use fiber optics technology that increases the speed and bandwidth of data transfer in smart grid applications. Incorporating IoE sensors, including fiber optics, is paramount to rehabilitating extensive IoE sensor data into practical information to distribute energy based on prices, availability, and demand for smart homes and electric vehicles. However, from energy generation to consumption, many nodes are incorporated. Therefore, security is a crucial challenge to processing accurate IoE sensor data for energy generation and consumption in smart cities. This paper presents blockchain-enabled, energy-efficient IoE smart grid architecture for smart homes and electric vehicle applications. The proposed architecture suggests blockchain-energy-efficient IoE sensors data scheduling (BEDS) algorithm schemes that consist of blockchain, smart grid, and vehicle and smart home schemes. The paper considers grid data based on sensors for different applications. The proposed system integrates fiber optics, collecting and offloading sensors to the grid for execution. This study aims to process IoE sensor data based on blockchain with a minimum processing time of 29% and less power consumption of 41%. Simulation results show that BEDS has less processing time and energy consumption than existing proof-of-work and proof-of-stake blockchain methods in smart grid networks.

Keywords: IoE sensors; Fiber optics; Production; Energy; Smart homes; Electric vehicles; Edge; Cloud; And smart grid (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123535

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