LAUSR

Applying blockchain technology to the Internet of Things (IoT) environment can significantly enhance the privacy protection of information and enable trusted sharing of data. However, the classic Proof-based blockchain systems have problems, such as unsatisfactory system throughput, low-consensus efficiency, and excessive computing resource consumption, making it difficult to directly apply them to the IoT environment. The recently proposed distributed ledger technology (DLT) represented by Tangle is designed based on the logical structure of the directed acyclic graph (DAG), which significantly improves the transaction confirmation delay and system throughput, making it more suitable for IoT scenarios. This article focuses on the performance and security of Tangle DLT in IoT applications with network instability. Such an unstable network environment can be caused by the predefined node working mode or signal interference, which leads to the status switching between online (work-mode) and offline (sleep-mode) of nodes or unstable data transmission. First, a Markov-chain-based model is established to analyze the time delay of block propagation in the underlying network under different status switching rates, different generation rates of blocks, different nodes’ average uplink bandwidths, and different number of neighbor nodes. Next, the impact of block propagation delay on the consensus efficiency and system throughput is analyzed. Furthermore, we also analyze the influence of block propagation delay on the attacker’s decision to conduct a double-spending attack under different network load, and deduce the suitable moment for the attacker to broadcast the parasite chain to maximize the probability of successful attack. Finally, through detailed numerical simulations, the experimental results comprehensively reveal the performance and security of the Tangle system in the unstable network environment. This article provides a valuable reference for the deployment and performance improvement of Tangle DLT in practical scenarios.