## 1 Introduction
### Related Work
[PERSON] et al., introduced a scalable PBFT algorithm that uses VRF (Verifiable Random Function) for selecting consensus nodes and simplifies the checkpoint protocol, making it suitable for dynamic networks [14]. [PERSON] [15] utilizes the RPCA (Ripple Protocol Consensus Algorithm), which is a high-performance BFT algorithm. Ripple's consensus is achieved only among validation nodes, and each validation node is preconfigured with a trusted node list called the Unique Node List (UNL). ABC [16] designed a PBFT consensus mechanism with a grouping scoring mechanism and an artificial bee colony optimization process. It uses the artificial bee colony algorithm to preselect a reliable set of nodes and then improves consensus efficiency through grouping mechanisms and a simplified PBFT submission process. The authors of [17] proposed an improved blockchain consensus algorithm based on a genetic algorithm. By combining the genetic algorithm with PBFT, they devised a fitness function for blockchain nodes, iteratively generating high-quality consensus node groups while limiting the consensus to a small portion. [PERSON] et al. [18] proposed a blockchain-based framework for mobile edge computing (B-MEC) for adaptive resource allocation and computation offloading in future wireless networks. The blockchainserves as an underlying system providing management and control functionalities [19]. By dividing nodes into groups and adopting RAFT for consensus within each group, the consensus process is expedited. The RAFT consensus mechanism elects a leader within each group. To ensure efficient consensus between leaders, the PBFT (Practical Byzantine Fault Tolerance) mechanism is employed. This combination guarantees consensus efficiency while maintaining security and reliability. Paxos is a consensus algorithm for distributed systems proposed by [PERSON] et al., in 1990 [20]. It is a message-passing-based algorithm that provides efficient fault tolerance and is widely recognized as one of the most effective solutions for achieving distributed consensus. However, Paxos is known for its complexity, steep learning curve, and difficulty in reproduction. After the introduction of RAFT, many researchers have conducted studies and advancements in the field. [PERSON] et al. [21] designed a hybrid consensus mechanism called LRPBFT, which combines the RAFT and PBFT algorithms using a link identification approach. Each subgroup adopts the RAFT consensus algorithm to form a committee and elect a leader, while the committee uses the PBFT algorithm for consensus and leader election. [PERSON] et al. [22] introduced monitoring nodes into the RAFT algorithm to enhance Byzantine fault-tolerance capabilities by analyzing the strengths and weaknesses of the PBFT and RAFT algorithms. These advancements and studies have further explored the RAFT algorithm, addressing its limitations and improving its efficiency and performance in various contexts and applications [23]. An improved PBFT algorithm was proposed to enhance the fault tolerance of the algorithm. However, to our knowledge, there is currently no research on considering RAFT to improve performance in the leader election stage of HBFT-based blockchain.