D2S-BFT: A General Performance Evaluation Framework for Sharded Blockchain Networks

Insights into Emerging Blockchain Scalability Approaches Through Layer-2 Solutions and Sharding Mechanisms for High Throughput Decentralised Systems

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.

H-PBFT: A Hierarchical and Credit-Aware PBFT Consensus Mechanism for Blockchain-Based Intelligent Transportation Systems

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.

Secure and Scalable Dynamic Blockchain Sharding via a Multi-Granularity Reputation Model

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.

Revolutionizing blockchain ecosystems: InternxtChain’s sharded storage & zk-SNARK security for secure, scalable, and decentralized solutions

The inherent challenge of balancing scalability, security, and decentralization – commonly termed the blockchain trilemma – continues to hinder the adoption of distributed systems. This paper presents InternxtChain, a decentralized storage framework designed to address this trilemma through a novel integration of erasure-coded sharding, zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs), and a sharded Proof-of-Storage consensus mechanism. By leveraging aggregated BLS-381 signatures and distributed redundancy protocols, the framework achieves a throughput of 2,800 transactions per second with a latency of 420 milliseconds across 1,024 nodes, surpassing Filecoin by a factor of 3.5 and Ethereum’s capacity by 165 times. The system maintains 99.9% data integrity even under adversarial conditions involving 30% Byzantine nodes. Additionally, InternxtChain reduces storage costs to $0.002 per gigabyte, representing an 85% reduction compared to centralized alternatives like AWS S3. Empirical evaluations demonstrate linear scalability to 4,200 transactions per second with 2,048 nodes, alongside hardware affordability at $180 per node. These advancements not only outperform decentralized platforms in throughput by 2.8 times but also ensure GDPR-compliant data sovereignty, positioning InternxtChain as a pioneering solution for Web3 ecosystems seeking to harmonize enterprise-grade performance with decentralized trustlessness.

T-DAA: Dynamic Account Allocation for Blockchain Sharding Based on Time-Decay Weighted Graph

Sharding is considered a promising solution to the scalability bottleneck of blockchain systems. However, the introduction of sharding mechanisms introduces two critical challenges: a high cross-shard transaction ratio and load imbalance. Most current graph-based allocation algorithms fall into two categories: either they treat all past transactions the same, which can let outdated data affect the system, or they use only the most recent transactions, which ignore useful long-term patterns and cause unnecessary cross-shard migrations. We introduce T-DAA to solve this problem by modeling account associations using a time-decay weighted graph. Using an exponential timedecay factor within a sliding window, the graph gives more importance to recent interactions. This approach filters out older, less relevant data and highlights strong connections between active accounts. Next, we present ThroughputBal, a reallocation algorithm based on the Maximum Spanning Tree (MST), to fix throughput and load imbalances. It identifies high-load shards and constructs communities rooted in active accounts to migrate excess workload to low-load shards. Finally, we introduce TXRatioBal, a cross-shard optimization algorithm that reduces the cross-shard transaction ratio while maintaining balanced loads. Tests on BlockEmulator with real Ethereum data show that T-DAA outperforms baselines across throughput, confirmation latency, and transaction pool backlog.

Blockchain-Based Spatial Registry and Management in Multi-User Mixed Reality