To solve the problem of inefficient energy allocation in traditional charging methods for electric vehicles, and considering the high concurrency of transactions in transaction-intensive scenarios, we propose an energy payment transaction scheduling solution for electric vehicles (EVs) based on off-chain computing. The solution utilizes blockchain to guarantee the security of inter-vehicle (V2V) energy payment and improves the transaction efficiency through an off-chain payment channel. We first construct a joint optimization problem aiming at selecting the optimal payment routing and setting the priority of payment forwarding. To solve this problem, we propose a multi-route multi-hop transaction scheduling algorithm (MRMH), which mainly contains two parts: a heuristic routing channel selection algorithm based on ant colony optimization for determining the optimal transaction paths, and a reinforcement learning-based (RL) relay forwarding algorithm for optimizing the relay selection during the transaction process. Finally, we verify the effectiveness of MRMH in the reliability and throughput of transactions by simulation experiments. The experiment results also show that MRMH can satisfy the demand for EVs charging in transaction-intensive scenarios while ensuring the security and efficiency of the transactions.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

An Energy Payment Transaction Scheduling Solution for Electric Vehicles Based on Off-Chain Computing

  • Ziyi Liu,
  • Yu Wu,
  • Qi Guo,
  • Qianwen Liu,
  • Yuzhen Zhang,
  • Xinfeng Deng,
  • Qiuping Li,
  • Xuanrui Xiong

摘要

To solve the problem of inefficient energy allocation in traditional charging methods for electric vehicles, and considering the high concurrency of transactions in transaction-intensive scenarios, we propose an energy payment transaction scheduling solution for electric vehicles (EVs) based on off-chain computing. The solution utilizes blockchain to guarantee the security of inter-vehicle (V2V) energy payment and improves the transaction efficiency through an off-chain payment channel. We first construct a joint optimization problem aiming at selecting the optimal payment routing and setting the priority of payment forwarding. To solve this problem, we propose a multi-route multi-hop transaction scheduling algorithm (MRMH), which mainly contains two parts: a heuristic routing channel selection algorithm based on ant colony optimization for determining the optimal transaction paths, and a reinforcement learning-based (RL) relay forwarding algorithm for optimizing the relay selection during the transaction process. Finally, we verify the effectiveness of MRMH in the reliability and throughput of transactions by simulation experiments. The experiment results also show that MRMH can satisfy the demand for EVs charging in transaction-intensive scenarios while ensuring the security and efficiency of the transactions.