2025/03/27 by Shuo Liu, Liu, Shuo, Minghui Xu +4
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Cryptography and Security (cs.CR) #Distributed #FOS: Computer and information sciences #Interconnection Networks and Systems #Parallel #Wireless Communication Networks Research #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2503.21279
openalex publication_date 2025/03/27 · openalex created_date 2025/10/11 · openalex updated_date 2026/07/28
Asynchronous Byzantine fault-tolerant (BFT) consensus protocols, known for their robustness in unpredictable environments without relying on timing assumptions, are becoming increasingly vital for wireless applications. While these protocols have proven effective in wired networks, their adaptation to wireless environments presents significant challenges. Asynchronous BFT consensus, characterized by its N parallel consensus components (e.g., asynchronous Byzantine agreement, reliable broadcast), suffers from high message complexity, leading to network congestion and inefficiency, especially in resource-constrained wireless networks. Asynchronous Byzantine agreement (ABA) protocols, a foundational component of asynchronous BFT, require careful balancing of message complexity and cryptographic overhead to achieve efficient implementation in wireless settings. Additionally, the absence of dedicated testbeds for asynchronous wireless BFT consensus protocols hinders development and performance evaluation. To address these challenges, we propose a consensus batching protocol (ConsensusBatcher), which supports both vertical and horizontal batching of multiple parallel consensus components. We leverage ConsensusBatcher to adapt three asynchronous BFT consensus protocols (HoneyBadgerBFT, BEAT, and Dumbo) from wired networks to resource-constrained wireless networks. To evaluate the performance of ConsensusBatcher-enabled consensus protocols in wireless environments, we develop and open-source a testbed for deployment and performance assessment of these protocols. Using this testbed, we demonstrate that ConsensusBatcher-based consensus reduces latency by 48% to 59% and increases throughput by 48% to 62% compared to baseline consensus protocols.