Abstract
Charging of Electric Vehicles (EVs) from stationary roadside charging points (CPs) that are connected to a smart grid constitute as unique transaction events. These events can thus be verified by and stored over a distributed blockchain over the grid, where the smart CPs themselves act as miners. However, mining being an inherently resource intensive task, the grid is expected to remain fairly loaded due to a high EV charging density. Hence, towards smooth EV adoption, in this work, we propose to reduce relevant mining overheads for such a blockchain over smart EV-utility grid using geographic segmentation of the miner set. Depending on the physical locations of the CPs and their connectivity graph, we divide an initially unsegmented mining cluster into several smaller clusters geographically, where each cluster verifies only their local transactions. This significantly reduces important mining parameters per-transaction and per-block, while achieving parallelism of block generation across segments. We argue that for blockchain transactions like EV charging that are coupled to their geographic source locations, it is sufficient to have smaller independent, but parallel mining segments. Through a detailed analysis, we also prove that reducing the mining segment size does not necessarily compromise on the blockchain security. We corroborate our claims through extensive experimental results, where the proposed solution achieves an average improvement of 48% with respect to CPU cycles expended and mining energy consumed per block and 45% with respect to mining time per block with half-sized segments as compared to an unsegmented miner set. Our experimental results further prove that the proposed segmentation outperforms other geographic clustering such as K-Means clustering for blockchain applications. Additionally, owing to parallel block generation, we show that by segmentation, the mining energy required per block is reduced from 19 J to about 0.02 J over the same grid, providing a significant energy efficiency.
