Parallel Byzantine Fault Tolerance Consensus for Blockchain Secured Swarm Robots

Abstract

ABSTRACT Establishing common knowledge about environmental conditions, task objectives, and coordination rules is crucial for improving the collaborative efficiency of swarm robots. In complex scenarios, relying on a centralized facility to maintain this knowledge is impractical, necessitating a decentralized approach. Blockchain technology offers a promising solution for decentralization and can tolerate some degree of malicious or malfunctioning entities. However, widely used blockchain approaches, such as those employed in Ethereum and relying on proof‐of‐work (PoW) or proof‐of‐authority (PoA), demand significant computational resources, rendering them impractical for swarm robotics applications. This paper introduces PTEE‐BFT, a novel parallel Byzantine fault tolerance protocol leveraging the trusted platform module (TPM). PTEE‐BFT employs a Unique Sequential Identifier Generator (USIG) to ensure the monotonicity, uniqueness, and order of messages, thereby reducing the number of communication phases and replicas required. This significantly enhances the efficiency and fault tolerance of the consensus process. Additionally, PTEE‐BFT implements parallel processing strategies to substantially increase blockchain system throughput. Furthermore, we develop an algorithm that enables the robot swarm to recognize attacks from a specific type of malicious robot known as Byzantine robots. Our experimental analysis and performance evaluation demonstrate that PTEE‐BFT achieves an optimal balance among performance, scalability, and fault tolerance, outperforming practical Byzantine fault tolerance (PBFT). Results from physical robots show that our approach significantly reduces computing overhead and accelerates consensus formation compared to baseline solutions. This represents a significant advancement in blockchain consensus mechanisms for swarm robotics.