Jul 2026· Annual International Computer Software and Applications Conference· pp. 2954-2959· 0 citations· 23 references
Abstract
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.
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
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.
Zhenhua Wang, Jiangang Hu, Xinmeng Wang et al.· Future Internet· 0 citations
Effective scaling of blockchain-enabled Industrial Internet of Things (IIoT) requires sharding that simultaneously ensures transaction locality, strict committee-size feasibility, and robustness against malicious node concentration. Existing methods often fail to balance this trilemma, risking either infeasible deployments or increased shard-takeover vulnerabilities. To address this, we propose GNN-OSS, a deployable sharding framework that decouples topology-aware preference learning from hard constraint enforcement. It first employs a trust-repulsion graph neural network to learn locality-aware preferences while discouraging low-trust nodes from collapsing into the same representation region. A Post-Hoc Capacity-Constrained Projection (PH-CCP) then maps these soft preferences into strictly feasible shard assignments. Finally, an entropy-driven Overlapping Sparse Scheme (OSS) selectively replicates boundary nodes to reduce residual cross-shard overhead without altering primary consensus membership. Evaluations demonstrate that, under the evaluated settings, GNN-OSS achieves a favorable performance–security trade-off. Against 20% malicious nodes, it substantially mitigates shard-takeover risks. Furthermore, it improves throughput by up to 33% over strictly feasible baselines and lowers the cross-shard ratio from 6.4% to 4.4% with minimal per-epoch overhead. Overall, GNN-OSS provides a practical sharding framework for open or hybrid blockchain-enabled IIoT environments.
Guangxia Xu, Zhuo Ye, Lu Wang et al.· IEEE Transactions on Network...· 0 citations
Blockchain technology is a distributed ledger technology that facilitates secure, transparent and decentralised transaction management between peer-to-peer networks without relying on a centralized authority. Despite its potential across various domains, scalability is a primary limitation in the development and evolution of blockchain technology. While Layer-2 execution frameworks and adaptive sharding techniques have shown significant results in overcoming the scalability limitation in blockchain technology, these techniques have generally been studied and developed in isolation. This study presents a comprehensive review of recent blockchain scalability techniques by categorizing these techniques and analyzing their performance characteristics in a comparative manner. The study critically evaluates the techniques in terms of their architecture design, operational mechanisms and performance characteristics while considering the associated trade-offs in terms of computation overhead, storage replication, hardware dependency, scalability degradation for larger node sizes and practical validation. The key insights demonstrate significant heterogeneity in terms of scalability methodologies adopted and environments used for experimentations. Also, enhanced throughput and reduced latency are often coupled with increased architectural complexity. The study highlights the absence of a unified and modular scalability framework capable of coherently integrating execution-layer optimization and shard management. The analytical synthesis presented a framework for understanding existing scalability paradigms and their architectural challenges for decentralised blockchain environments.
Pandiselvi B, D.Balakrishnan· International Conference Com...· 0 citations
The widespread adoption of decentralized identity (DID) is constrained by blockchain scalability issues. Mainstream Layer 1 blockchains are costly, while generic Layer 2 Rollups face the “Noisy Neighbor” problem, where identity operations compete with DeFi traffic, causing unpredictable delays. To address this, we propose EM-DID, an Elastic Multiinstance DID Architecture. Unlike static chains, EM-DID treats Layer 2 execution environments as dynamic resources. The system employs three novel mechanisms: an Auto-Scaling Manager utilizing a Warm Pool strategy for near-zero coldstart latency and Hysteresis to prevent resource oscillation; a QoS-Aware Scheduling Algorithm that routes requests based on cost-latency trade-offs; and a Hierarchical State Aggregation Protocol that compresses proofs from multiple instances into a single Layer 1 transaction. Experiments demonstrate that EM-DID achieves linear scalability. While a single simulation instance sustains 600 TPS constrained by the testbed environment, the architecture supports horizontal scaling to thousands of TPS by adding instances without degradation. The architecture reduces gas costs by 99.76% compared to Layer 1 and minimizes average latency by approximately 94% through intelligent routing. EM-DID provides a viable path for deploying high-frequency, self-sovereign identity services in scenarios such as the Internet of Things (IoT).
Yang Liu, Yuanchao Liu, Zihang Yin· Annual International Compute...· 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
