A Double Auction for Charging Scheduling among Vehicles Using DAG-Blockchains
Jianxiong Guo, Xingjian Ding, Weili Wu, Ding-Zhu Du
TL;DR
Electric vehicles require rapid, secure, and scalable charging coordination across distributed charging stations. The authors present a Blockchain-based Charging Scheduling (BCS) framework built on a DAG-based blockchain to enable decentralized trading, with a central manager conducting a constrained multi-item double auction between EVs (buyers) and CSs (sellers). They introduce two auction mechanisms: Truthful Mechanism for Charging (TMC), which guarantees IR, budget balance, truthfulness, and polynomial-time complexity, and Efficient Mechanism for Charging (EMC), which improves system efficiency at the cost of full truthfulness for buyers. The framework preserves privacy and security via cryptographic identities and DAG transactions, and simulations demonstrate that EMC substantially increases trades and reduces runtime, offering a practical option for real-world EV charging markets.
Abstract
Electric Vehicles (EVs) are becoming more and more popular in our daily life, which replaces traditional fuel vehicles to reduce carbon emissions and protect the environment. EVs need to be charged, but the number of charging piles in a Charging Station (CS) is limited and charging is usually more time-consuming than fueling. According to this scenario, we propose a secure and efficient charging scheduling system based on a Directed Acyclic Graph (DAG)-blockchain and double auction mechanism. In a smart area, it attempts to assign EVs to the available CSs in the light of their submitted charging requests and status information. First, we design a lightweight charging scheduling framework that integrates DAG-blockchain and modern cryptography technology to ensure security and scalability during performing scheduling and completing tradings. In this process, a constrained multi-item double auction problem is formulated because of the limited charging resources in a CS, which motivates EVs and CSs in this area to participate in the market based on their preferences and statuses. Due to this constraint, our problem is more complicated and harder to achieve truthfulness as well as system efficiency compared to the existing double auction model. To adapt to it, we propose two algorithms, namely Truthful Mechanism for Charging (TMC) and Efficient Mechanism for Charging (EMC), to determine an assignment between EVs and CSs and pricing strategies. Then, both theoretical analysis and numerical simulations show the correctness and effectiveness of our proposed algorithms.