Simulation results show that compared with standard PBFT, Q-PBFT, and APBFT, H-PBFT exhibits significant advantages in consensus latency, throughput, and view switching recovery time, and maintains high system robustness even in complex network environments with malicious nodes.
Abstract
To address the risks of centralized single-point failures and data privacy leaks associated with massive data storage in Intelligent Transportation Systems (ITS) and Vehicle-to-Everything (V2X) environments, this paper proposes a distributed secure storage architecture based on blockchain. However, traditional Practical Byzantine Fault-Tolerant (PBFT) algorithms suffer from scalability bottlenecks in large-scale dynamic networks, such as high communication overhead and low consensus efficiency. Therefore, this paper designs a hierarchical and reputation-aware improved consensus mechanism (H-PBFT). First, this mechanism introduces a geographical location grouping strategy, dividing all network nodes into several local consensus groups and leveraging edge computing characteristics to achieve rapid consensus within each group. Second, a multi-dimensional reputation evaluation model (comprehensively considering historical behavior, performance, and availability) is constructed to dynamically elect representative nodes from each group to participate in global consensus, thereby significantly reducing the communication complexity from O(N2). Simulation results show that compared with standard PBFT, Q-PBFT, and APBFT, H-PBFT exhibits significant advantages in consensus latency, throughput, and view switching recovery time, and maintains high system robustness even in complex network environments with malicious nodes.
A blockchain-based dynamically adaptive restructuring framework that enables real-time IoV cluster restructuring by splitting overloaded IoVs to reduce communication overhead, or merging nearby IoVs to optimize resource utilization, offering a proactive, adaptive security paradigm for intelligent transportation frameworks.
Jiawei Shi, Yebo Feng, Konglin Zhu et al.· ACM Transactions on Internet...· 0 citations
Elastic Proof-of-Location Byzantine Fault Tolerance is proposed, a privacy-preserving and location-aware blockchain consensus framework for IoT systems that reduces communication overhead and improves consensus efficiency compared with conventional PBFT-based approaches while strengthening resilience against location-based and identity-based attacks.
Yunus Kareem, D. Djenouri, Essam Ghadafi· Future Internet· 0 citations
This study qualitatively examines ten widely used consensus algorithms within the research context of Bintan, Riau Islands, Indonesia and indicates that DAG/IOTA and Hashgraph achieve the highest throughput with minimal latency, making them suitable for IoT and enterprise-scale applications.
Dodi Setiawan¹, Sri Sutjiningtyas², A. Eka et al.· West Science Information Sys...· 0 citations
Blockchain technology enables decentralized trust, yet traditional blockchain networks face critical scalability limitations under large-scale deployments. Sharding improves throughput through parallel processing, but existing sharded BFT architectures still suffer from severe hierarchical coupling between shards and the verification committee. Moreover, the complex asynchronous competition and backoff/retransmission dynamics in sharded blockchain services remain largely unmodeled, leaving the network-level steady-state behavior of sharded blockchains poorly understood. To address these challenges, we propose D2S-BFT, a novel Decoupled Double-Star Byzantine Fault-Tolerant architecture, which physically decouples local intra-shard consensus from global verification. For rigorous performance evaluation, we establish a randomized-service double-star service system and cast the cross-shard competition mechanism as a finite-source Markov chain. We derive the state transition probability matrix under general load conditions, compute the extended sojourn time, and construct an end-to-end transaction on-chain latency equation that explicitly incorporates encryption overhead, network delay, and queuing delay. The resulting D2S queuing model, expressed in the non-classical Kendall notation L/G/n=2/inf/L-RSS, provides strict theoretical boundary constraints on system performance. It demonstrates that D2S-BFT can effectively alleviate transaction congestion and ensure robust operation, while also laying a rigorous analytical foundation for model-driven configuration optimization in large-scale dynamic blockchain environments.
Ji-Qiang Liu, Lijun Sun, Xiao Chen et al.· 2026 International Conferenc...· 0 citations
Sharding technology divides the blockchain network into multiple parallel-processing subnetworks, achieving high throughput and scalability. However, it also faces challenges, including the risk of 51% attack caused by malicious node clustering and systemic load imbalances. While reputation mechanisms are widely employed to mitigate these risks, existing approaches remain constrained by unidimensional evaluations. Specifically, most studies focus on node behavior and assess node security metrics, neglecting node performance metrics and node heterogeneity. To address these challenges, this paper presents a multi-granularity reputation model to quantify the efficiency and reliability of nodes. This model accounts for the performance and security differences arising from node heterogeneity and behavioral dynamics. Based on this model, we further propose a neighborhood-constrained simulated annealing-based node partition algorithm, NCSA-NP, that achieves balanced security and performance across shards. Experimental results demonstrate that the proposed approach achieves significant improvements in throughput and latency compared to other baselines.
Jie Li, Zhihao Guo, Yibing Li et al.· Annual International Compute...· 0 citations
The introduction of blockchain technology has revolutionized decentralized systems. Blockchain enables peer-to-peer (P2P) transactions to be trustworthy and transparent. However, existing traditional consensus mechanisms such as Proof of Work (PoW) and Proof of Stake (PoS) have significant issues regarding computational costs, efficiency, and centralization, which severely limit their adoption in resource-constrained environments. For instance, in an industrial Internet of Things (IoT) network or a smart metering infrastructure, devices operate on strict energy budgets and cannot participate in compute-heavy PoW mining. They also lack the capital to lock up financial stakes for PoS. To address those limitations, randomized consensus mechanisms such as Pure Proof of Stake (PPoS) and Proof of Luck (PoL) were introduced. Yet these methods have issues with fairness, secure randomness generation, and cost efficiency. This paper proposes a new randomized proposer selection mechanism for blockchain consensus called Proof of Proximity (PoP) that enhances unpredictability, fairness, decentralization, and security. PoP replaces cryptographic randomness beacons with transaction-derived entropy and distance minimization. This enables fair, unpredictable proposer selection without relying on Verifiable Random Functions (VRFs), trusted hardware, or stakebased weighting, maintaining low computational overhead. The mechanism is ideal for IoT networks where resource consumption and security are critical. Experimental and comparative analysis results prove that PoP achieves improved fairness, decentralization, security, and low resource consumption, making it suitable for resource-constrained decentralized systems.
Nelum Ranawaka, L.A.M.S. Gawesh, G.O. Sundarasekara et al.· Annual International Compute...· 0 citations
