In timing-sensitive blockchain applications, such as decentralized finance (DeFi), achieving first-come-first-served (FCFS) transaction ordering among decentralized nodes is critical to prevent frontrunning attacks. Themis [CCS'23], a state-of-the-art decentralized FCFS ordering system, has become a key reference point for high-throughput fair ordering systems for real-world blockchain applications, such as rollup chains and decentralized sequencing, and has influenced the design of several subsequent proposals. In this paper, we critically analyze its core system property of practical batch-order fairness and evaluate the frontrunning resistance claim of Themis. We present the Ambush attack, a new frontrunning technique that achieves nearly 100% success against the practical batch-order fair system with only a single malicious node and negligible attack costs. This attack causes a subtle temporary information asymmetry among nodes, which is allowed due to the heavily optimized communication model of the system. A fundamental trade-off we identify is a challenge in balancing security and performance in these systems; namely, enforcing timely dissemination of transaction information among nodes (to mitigate frontrunning) can easily lead to non-negligible network overheads (thus, degrading overall throughput performance). We show that it is yet possible to balance these two by delaying transaction dissemination to a certain tolerable level for frontrunning mitigation while maintaining high throughput. Our evaluation demonstrates that the proposed delayed gossiping mechanism can be seamlessly integrated into existing systems with only minimal changes.
Abstract Distributed Software Define Network (DSDN) offers to eliminate the single point of failure present in the centralized SDN controller. The main concept is to have numerous controllers that can share the burden on the network, and one controller can take over another controller when it breaks. In this study, we work on an Opendaylight-based completely distributed system to deal with issues of the controller's central processing unit (CPU) consumption being uneven. Every controller administers its own domain therefore sharing the burden across the network's controllers. To update the flow rules and broadcast new rules to all the controllers at once, maintaining the consistency of the controller's rule set, we create an application ledger that maintains a distributed ledger. Results demonstrate that, in addition to ensuring the uniformity of inventory shards across all controllers in the system, our work presented an increase with throughput reaching 40% and the bandwidth of controller's communication is less with almost 31%.
The paradigm of enterprise analytics is undergoing a fundamental shift from centralized, reactive reporting to distributed, proactive intelligence. This review article evaluates the integration of machine learning models within SAP business intelligence frameworks operating across multi-cloud and hybrid environments. We analyze how the transition toward a federated data architecture, facilitated by SAP Datasphere, enables the deployment of high-performance neural networks without the traditional constraints of data replication. The study specifically examines the efficacy of Long Short-Term Memory units for temporal forecasting in SAP Integrated Business Planning and the role of unsupervised learning models in real-time financial anomaly detection. Furthermore, we explore the rise of augmented analytics and natural language processing in democratizing data access, alongside the operational necessity of MLOps to mitigate model drift in volatile global markets. The review also addresses critical technical and strategic barriers, including data latency across distributed cloud nodes, the harmonization of structured and unstructured data, and the evolving landscape of global data sovereignty. By synthesizing current performance benchmarks with future directions such as agentic intelligence and the integration of carbon accounting through the green ledger, this research provides a roadmap for architecting autonomous analytical ecosystems. We conclude that the convergence of machine learning and distributed cloud infrastructure is the primary catalyst for transforming raw enterprise data into a strategic, self-optimizing asset.
Blockchain interoperability is increasingly recognized as the centerpiece for robust interactions among decentralized services. Blockchain ledgers are generally tamper-proof and thus enforce non-repudiation for transactions recorded within the same network. However, such a guarantee does not hold for cross blockchain transactions. When disruptions occur due to malicious activities or system failures within one blockchain network, foreign networks can take advantage by denying legitimate claims or mounting fraudulent liabilities against the defenseless network. In response, this paper introduces InterSnap, a novel blockchain snapshot archival methodology, for enabling auditability of cross blockchain transactions, enforcing non-repudiation. InterSnap introduces cross-chain transaction receipts that ensure their irrefutability. Snapshots of ledger data along with these receipts are utilized as non-repudiable proof of bilateral agreements among different networks. InterSnap enhances system resilience through a distributed snapshot generation process, need-based snapshot scheduling process, and archival storage and sharing via decentralized platforms. Through a prototype implementation based on Hyperledger Fabric, we conducted experiments using on-premise machines, AWS public cloud instances, as well as a private cloud infrastructure. We establish that InterSnap can recover from malicious attacks while preserving cross chain transaction receipts. Additionally, our proposed solution demonstrates adaptability to increasing loads while securely transferring snapshot archives with minimal overhead.
In complex environments such as those incorporating distributed and edge computing, middleware plays a critical role in meeting the communication and performance requirements of distributed systems by providing communication flow and integration capabilities. Its inherent advantages, such as abstraction of complexities, enhanced interoperability and scalability, make it ideal for managing tasks such as federated learning in edge AI environments. In addition, by supporting secure and energy-efficient operations, the middleware fosters sustainability, enabling green blockchain solutions and low-power distributed ledger technologies (DLTs) to thrive for managing dynamic ecosystems such as dAIEDGE. This deliverable D5.3, "Middleware prototype" presents the first version of dAIEDGE middleware. This work has been developed during the first year of dAIEDGE project from M4 to M16. In general, the document outlines the first version of the middleware developed collaboratively with task partners, by the University of Salamanca (USAL) as part of Task T5.2, "Middleware and Networks for Edge AI," within the dAIEDGE project. This task reflects a joint effort involving multiple participants, including BCA, BTH, CETIC, KUL, VICOM, and UEDIN.
Sr IT Developer, First Horizon Bank, Memphis, TN, USA, Rushikesh Anantrao Deshpande
The article examines methods for optimizing PL/SQL queries in distributed banking databases, emphasizing the transition from static rule-based mechanisms to adaptive, learning-driven architectures. The study’s relevance is defined by the increasing complexity of financial data environments that require real-time consistency, fault tolerance, and intelligent workload distribution. The research synthesizes results from seven recent works published between 2021 and 2025, covering neural cost modeling, heuristic algorithms, hybrid plan enumeration, and visualization-based diagnostics. Special attention is devoted to learned cost models and metaheuristic strategies that enhance selectivity estimation, reduce latency, and stabilize throughput in distributed ledger systems. The methodological framework integrates comparative analysis, systematization, and critical evaluation of hybrid, heuristic, and learning-based optimizers. The findings reveal a multi-layered optimization model that combines probabilistic inference, robust plan selection, and heuristic refinement. The conclusions underscore the practical applicability of adaptive PL/SQL optimization for high-volume banking infrastructures and data-intensive financial analytics.
Distributed Ledger Technologies (DLTs) underpin Digital Circular Economy (DCE) systems that rely on efficient IoT data flows. Shimmer, a DAG-based DLT optimized for IoT, enables feeless transactions with parallel validation through its tip-selection mechanism. On such ledgers, message fragmentation induces a latency–throughput tradeoff as per-block cost rises with parallel validation. Such efficiency lowers energy and congestion, supporting DCE objectives. Yet, end-users cannot control payload size or network load, leading to unpredictable latency and high CPU use on submitting devices, increasing energy consumption. Existing approaches mostly modify ledger internals, overlooking adaptivity or end-user policies. We introduce ABS-TD3, an offline-to-online TD3 agent that receives the total message size and outputs the optimal per-block size for balancing latency and energy-efficient CPU utilization. The agent is pre-trained offline on real data with Retrieval Augmentation and adaptive weights for improved decision making, then transitioned online with prioritized replay and a novelty bonus, balancing exploitation-exploration, yielding stable adaptivity compared to standard RL approaches. ABS-TD3 is implemented on Shimmer and can integrate with future Tangle-based forks of pre-IOTA-Rebased frameworks, exposing the same client-side controls. ABS-TD3 is evaluated on Shimmer by submitting 8 message sizes ranging from 5KB to 100KB, under the 32 KB block-size limit, with 250 iterations per size via IOTA-SDK. Against max, min, random, and fixed-weight baselines, it reduces median latency by about 9 % to 12 % and median CPU utilization by about 12 % to 17 % versus max and random policies, enabling efficient IoT data submission for DCE platforms without altering DLT infrastructure.
Ethereum is currently the main blockchain ecosystem providing decentralised trust guarantees for applications ranging from finance to e-government. A common criticism of blockchain networks has been their energy consumption and operational costs. The switch from Proof-of-Work (PoW) protocol to Proof-of-Stake (PoS) protocol has significantly reduced this issue, though concerns remain, especially with network expansions via additional layers. The ERC-4337 standard is a recent proposal that facilitates end-user access to Ethereum-backed applications. It introduces a middleware called a bundler, operated as a third-party service, where part of its operational cost is represented by its power consumption. While bundlers have served over 500 million requests in the past two years, fewer than 15 official bundler providers exist, compared to over 100 regular Ethereum access providers. In this paper, we provide a first look at the active power consumption overhead that a bundler would add to an Ethereum access service. Using SmartWatts, a monitoring system leveraging Running Average Power Limit (RAPL) hardware interfaces, we empirically determine correlations between the bundler workload and its active power consumption.
A digital revolution is taking place in healthcare due to rising patient data volumes, concerns about privacy and security, and the need for interoperable solutions. The demand for trustworthy, scalable, and interoperable technologies has become essential in this fast-growing healthcare industry. Conventional centralised systems regularly encounter challenges meeting these requirements because of problems including storage structure, data privacy, security vulnerabilities, network complexity, and lack of scalability. Additionally, current blockchain implementations frequently face challenges with interoperability, trust management among several healthcare stakeholders, and throughput bottlenecks. To overcome these challenges, this paper introduces a novel framework called LIVER: a Lightweight Infrastructure for Verifiable Electronic Records that integrates Blockchain, InterPlanetary File System (IPFS), Edge computing, and Internet of Medical Things (IoMT) to address these issues. Distributed processing based on edge computing and IPFS, cryptographic methods, blockchain consensus mechanisms, and an immutable ledger allows it to be scalable, secure, interoperable, and boast tamper-proof data integrity. Furthermore, a unique queueing approach has been implemented to improve operational efficiency, which controls patient flow, decreases wait times, maximises resource utilisation, minimises healthcare delays, and enhances the patient experience. Finally, based on the experimental evaluation results, the LIVER framework reduces ledger size, facilitates enhanced data sharing, and improves the healthcare system’s efficiency, scalability, security, and performance. The goal is to provide a framework that can handle the computational and operational limitations of existing healthcare systems while still protecting patient privacy and allowing for scalability.
Carlos Cardoso, Caio Silva, Alan Veloso, Jeffson Sousa · 5 authors
As Distributed Ledger Technologies (DLTs) mature into production-grade systems, a critical gap emerges between protocol-level benchmarking and application-centric performance testing. While specialized tools like Hyperledger Caliper excel at measuring core on-chain metrics, they are less suited for evaluating the end-to-end performance of applications that interact with the DLT through an intermediary API layer. This paper addresses this gap by proposing a three-tier, API-driven framework that enables mature, general-purpose load testing tools, such as Apache JMeter, to realistically assess a Hyperledger Besu network’s performance from an application’s perspective. The core of our solution is a custom API server that provides essential services like atomic nonce management and dynamic load balancing. Our comparative analysis demonstrates that while Caliper may report higher end-to-end throughput under specific conditions, our framework induces a significantly more substantial and evenly distributed load, revealing a more accurate picture of the network’s true processing capacity. Furthermore, our approach captures API-layer latency—a crucial metric for client-perceived responsiveness—which proved to be an order of magnitude lower than the on-chain finality measured by Caliper. This work validates a reusable architectural pattern for testing DLTs within a realistic application stack, bridging the gap between protocol benchmarking and real-world performance engineering.
This paper investigates performance bottlenecks of consortium blockchains under high-throughput and low-latency requirements, focusing on excessive storage burden on full nodes and redundant computation in transaction validation. Based on consortium blockchain, a novel architecture named Server-Side Core Chain (SSC) is proposed. In this architecture, the core functions of blockchain ledger data storage and smart contract execution are delegated from decentralized consensus nodes to a server cluster jointly managed and trusted by consortium members. The consensus node layer is restructured into a lightweight ``Consensus and Audit Network,” dedicated to transaction ordering and state commitment verification. This paper elaborates on the design principles, operational workflow, and security model of the SSC architecture. Theoretical analysis and prototype experiments demonstrate that the architecture significantly enhances the transaction processing capacity of consortium blockchains (experimental results show a throughput improvement of more than 18 times), greatly reduces the entry barriers and operational costs for member nodes (storage overhead reduced by over 99%), and ensures the verifiability of off-chain computations and data privacy through cryptographic commitments and zero-knowledge proofs [1]. The SSC architecture offers a new solution for deploying consortium blockchains in large-scale applications, including finance, supply chain management, and e-government.
Vladyslav Nekriach, Sidi Mohamed Beillahi, C. Li, Peilun Li · 7 authors
This paper introduces HEMVM, an innovative heterogeneous blockchain framework that seamlessly integrates diverse virtual machines (VMs), including the Ethereum Virtual Machine (EVM) and the Move Virtual Machine (MoveVM), into a unified system. This integration facilitates interoperability while retaining compatibility with existing Ethereum and Move toolchains by preserving high-level language constructs. HEMVM's unique cross-VM operations allow users to interact with contracts across various VMs using any wallet software, effectively resolving the fragmentation in user experience caused by differing VM designs. Our experimental results demonstrate that HEMVM is both fast and efficient, incurring minimal overhead (less than 4.4 %) for intra-VM transactions and achieving up to 9300 TPS for cross-VM transactions. Our results also show that the cross-VM operations in HEMVM are sufficiently expressive to support complex decentralized finance interactions across multiple VMs. Finally, the parallelized prototype of HEMVM shows performance improvements up to 44.8 % compared to the sequential version of HEMVM under workloads with mixed transaction types.
This study tackles the computational challenges of solving Markov Decision Processes (MDPs) for a restricted class of problems. It is motivated by the Last Revealer Attack (LRA), which undermines fairness in some Proof-of-Stake (PoS) blockchains such as Ethereum (\$400B market capitalization). We introduce pseudo-MDPs (pMDPs) a framework that naturally models such problems and propose two distinct problem reductions to standard MDPs. One problem reduction provides a novel, counter-intuitive perspective, and combining the two problem reductions enables significant improvements in dynamic programming algorithms such as value iteration. In the case of the LRA which size is parameterized by $κ$ (in Ethereum's case $κ$= 325), we reduce the computational complexity from $O(2^κκ^{2^{κ+2}})$ to $O(κ^4)$ (per iteration). This solution also provide the usual benefits from Dynamic Programming solutions: exponentially fast convergence toward the optimal solution is guaranteed. The dual perspective also simplifies policy extraction, making the approach well-suited for resource-constrained agents who can operate with very limited memory and computation once the problem has been solved. Furthermore, we generalize those results to a broader class of MDPs, enhancing their applicability. The framework is validated through two case studies: a fictional card game and the LRA on the Ethereum random seed consensus protocol. These applications demonstrate the framework's ability to solve large-scale problems effectively while offering actionable insights into optimal strategies. This work advances the study of MDPs and contributes to understanding security vulnerabilities in blockchain systems.
The problem addressed in this study is the lack of a proper conceptualization of the Distributed Ledger Technology-based Central Bank Digital Currency technical language that guides central banks and their stakeholders in the platforms design and implementation.This research aims to improve the DLT-based CBDC knowledge, proposing a human-centered reference model.We use Design Science Research methodology combined with other research methods.The literature has not provided a reference model that can be used to improve the design of the CBDC system to meet regulatory requirements.This study fills the gap in the literature by presenting a human-centered reference model for DLT-based CBDC that serves as a decision-aid tool to study citizens' needs and behaviors, to design user experience, to improve alignment between cultural values and policy roles, and to facilitate communication between experts and stakeholders on currency digitalization process.
Moderne Blockchains verarbeiten mittlerweile Zehntausende Transaktionen pro Sekunde. Mit steigendem Durchsatz wachsen jedoch auch die Anforderungen für die Verifikation von Blockchains. Zentralisierte Node-as-a-Service (NaaS)-Anbieter (z.B. Infura oder Alchemy) bieten zwar praktische APIs, schaffen jedoch zusätzliche Vertrauensabhängigkeiten und bergen Risiken in Bezug auf Datenschutz und Zensurfreiheit. Ein selbst betriebener Full Node ermöglicht Datenzugang ohne zusätzliche Vertrauensannahmen, ist für die meisten Nutzerinnen und Nutzer jedoch aufgrund des hohen Ressourcenbedarfs kaum praktikabel. Im Gegensatz dazu arbeiten Light Clients deutlich ressourcenschonender, können dafür den vollständigen Anwendungszustand nicht rekonstruieren. Ein neuer Ansatz, der als Sparse Client (bzw. Partially Stateless Client) bekannt ist, ermöglicht dagegen die verifizierbare Überwachung eines Teilzustands der Blockchain, indem ausschließlich jene Transaktionen heruntergeladen, ausgeführt und gespeichert werden, die diesen Teilzustand lesen oder verändern. Bisher fehlt eine fundierte wissenschaftliche Aufarbeitung: Die einzige verfügbare Arbeit zu diesem Thema weist deutliche Limitierungen auf und wurde weder implementiert noch umfassend evaluiert. In dieser Arbeit präsentieren wir zwei Sparse-Client-Protokolle für EVM-kompatible Blockchains: Sparseth für zustandsbasierte Synchronisation und Eventeth für ereignis-basierte Synchronisation. Beide Protokolle ermöglichen es Nutzerinnen und Nutzern, überprüfbare Teilmengen der globalen Transaktions- oder Ereignissequenz und des damit verbundenen Zustands zu verwalten, ohne dass zusätzlicher Validator-Aufwand erforderlich ist. Sparseth nutzt einen Interaktionszähler, um sicherzustellen, dass keine relevanten Transaktionen ausgelassen werden, während Eventeth eine kryptographische Hash-Kette einsetzt, um die Integrität und Vollständigkeit der Ereignisse zu gewährleisten. Im Gegensatz zu bestehenden Ansätzen arbeiten beide Protokolle vollständig auf der Ausführungsschicht und sind mit EVM-basierten Blockchains kompatibel. Unsere formale Analyse zeigt, dass beide Protokolle im angenommenen Widersacher-Modell Sicherheit, Liveness und spärliche Gültigkeit garantieren. Unsere Implementierung in Go demonstriert die praktische Umsetzbarkeit: Event Nodes senken den Bandbreitenbedarf um über 95%, Sparse Nodes reduzieren die auszuführenden Transaktionen um 92% gegenüber Full Nodes. Die Gas-Kosten steigen um 4-16% für typische dApp-Transaktionen, ein Mehraufwand, der sich durch L2-Lösungen und ökonomische Anreize weiter mindern lässt.
Network Systems, AT&T, United States, Amar Gurajapu, Vardhan Garimella, United States Intellibus
ABSTRACT: Distributed cloud services across multiple providers demand consistent identity verification and policy enforcement. Centralized IAM and policy managers introduce single points of failure, limited auditability, and latency. We propose BC-IdPol, a blockchain-based framework that stores identities and governance policies on a permissioned ledger. Smart contracts enforce registration, authentication, and policy retrieval. Off-chain cloud agents query the chain for runtime decisions. In experiments over a three-cloud prototype (Azure, AWS, GCP) on Hyperledger Fabric, BC- IdPol achieved: 99.9 % tamper-resistance (vs. 0 % baseline) 45 ms median identity lookup latency (vs. 18 ms centralized API) 60 ms median policy fetch time (vs. 20 ms baseline) 1,800 req/sec enforcement throughput (vs. 2,200 req/sec) We detail architecture, smart-contract design, mermaid diagrams, evaluation results, limitations, and future work.
The increasing demand for cloud computing services has led to the rapid expansion of cloud data centers, which consume significant amounts of energy and contribute substantially to global CO2 emissions. As the IT industry grows, the environmental impact of these data centers becomes an urgent concern. Green Cloud Computing (GCC) has emerged as a solution to mitigate this impact by focusing on energy efficiency and reducing carbon footprints while maintaining the necessary functionality and performance of cloud infrastructures. However, traditional blockchain consensus algorithms such as Proof of Work (PoW) and Proof of Stake (PoS) face limitations regarding energy consumption and scalability, which exacerbates the environmental burden. This study proposes a quantum-inspired blockchain consensus algorithm designed to optimize energy consumption and reduce latency in cloud data centers. By integrating quantum principles such as superposition and entanglement, the algorithm enhances task scheduling and resource utilization, enabling more energy-efficient operations without sacrificing performance. Simulations in a green cloud environment showed that the quantum-inspired algorithm resulted in up to a 30% reduction in energy usage compared to traditional consensus methods, with a 40% improvement in consensus processing time. These results suggest that quantum-inspired algorithms hold significant potential for enhancing the sustainability of cloud infrastructures by improving energy efficiency and scalability. Furthermore, this study discusses the feasibility of implementing quantum-inspired algorithms on classical hardware, addressing challenges in scalability and integration into existing blockchain frameworks. The findings provide valuable insights into the potential of quantum-inspired technologies to drive energy-efficient solutions in cloud computing.
Adam Zahir, Milan Groshev, Carlos J. Bernardos, Antonio de la Oliva
Edge computingbrings computation near end users, enabling the provisioning of novel use cases. To satisfy end-user requirements, the concept ofedge federationhas recently emerged as a key mechanism for dynamic resources and services sharing across edge systems managed by different administrative domains. However, existing federation solutions often rely on pre-established agreements and face significant limitations, including operational complexity, delays caused by manual operations, high overhead costs, and dependence on trusted third parties. In this context, Distributed Ledger Technologies (DLTs) such asblockchaincan create dynamic federation agreements that enable service providers to securely interact and share services without prior trust. This article first describes the problem of edge federation, using the standardized ETSImulti-access edge computing (MEC)framework as a reference architecture, and how it is being addressed. Then, it proposes a novel solution usingblockchainandsmart contractsto enable distributed MEC systems to dynamically negotiate and execute federation in a secure, automated, and scalable manner. We validate our framework’s feasibility through a performance evaluation using a private Ethereum blockchain, built on the open-source Hyperledger Besu platform. The testbed includes a large number of MEC systems and compares two blockchain consensus algorithms. Experimental results demonstrate that our solution automates the entire federation lifecycle-from negotiation to deployment–with a quantifiable overhead, achieving federation in approximately 18 seconds in a baseline scenario. The framework scales efficiently in concurrent request scenarios, where multiple MEC systems initiate federation requests simultaneously. This approach provides a promising direction for addressing the complexities of dynamic, multi-domain federations across the edge-to-cloud continuum.
Non-Fungible Tokens (NFTs) have emerged as a transformative blockchain-based technology, enabling unique digital ownership and novel applications across art, gaming and Decentralized Finance (DeFi).However, the rapid evolution of NFT ecosystems has exposed critical challenges in scalability, security and interoperability, driven by the underlying blockchain architectures and software design paradigms.This article presents a systematic review of state-of-the-art blockchain architectures supporting NFTs, analyzing Layer-1 and Layer-2 solutions, consensus mechanisms and smart contract design patterns.We further explore software design best practices for NFT platforms, including gas optimization, upgradeability and anti-fraud mechanisms.Through a comparative analysis of Ethereum, Solana, Flow and Layer-2 frameworks like Polygon, we identify trade-offs in decentralization, throughput and cost.Finally, we highlight open challenges and future directions, such as cross-chain interoperability and energy-efficient NFT minting.This work serves as a comprehensive reference for researchers and practitioners aiming to advance NFT infrastructure.
Mohammed Ziaul Haider, Tayyaba Noreen, Mishah Uzziél Salman, Marcos Dias de Assunção · 5 authors
Cross-chain bridges and oracle DAOs represent some of the most vulnerable components of decentralized systems, with more than 2.8 billion lost due to trust failures, opaque validation behavior, and weak incentives. Current oracle designs are based on multisigs, optimistic assumptions, or centralized aggregation, exposing them to attacks and delays. Moreover, predictable committee selection enables manipulation, which threatens data integrity across chains. We propose V-ZOR, a verifiable oracle relay that integrates zero-knowledge proofs, quantum-grade randomness, and cross-chain restaking to mitigate these risks. Each oracle packet includes a Halo 2 proof verifying that the reported data was correctly aggregated using a deterministic median. To prevent committee manipulation, VZOR reseeds its VRF using auditable quantum entropy, ensuring unpredictable and secure selection of reporters. Reporters stake once on a shared restaking hub; any connected chain can submit a fraud proof to trigger slashing, removing the need for multisigs or optimistic assumptions. A prototype in Sepolia and Scroll achieves sub-300k gas verification, one-block latency, and a $\mathbf{1 0} \times$ increase in collusion cost. V-ZOR demonstrates that combining ZK attestation with quantum-randomized restaking enables a trust-minimized, high-performance oracle layer for cross-chain DeFi.
In recent years, blockchain consensus mechanisms have evolved significantly from the original proof-of-work design, transitioning towards more efficient and scalable alternatives. This paper presents a comprehensive review and analysis framework for blockchain consensus mechanisms based on a systematic examination of 200+ publications. We categorize consensus mechanisms into four performance-oriented groups: high throughput, strong security, low energy, and flexible scaling, each addressing specific trade-offs in the blockchain trilemma of decentralization, security, and scalability. Through quantitative metrics including transactions per second, energy consumption, fault tolerance, and communication complexity, we evaluate mainstream mechanisms. Our findings reveal that no single consensus mechanism optimally satisfies all performance requirements, with each design involving explicit trade-offs. This paper provides researchers and practitioners with a structured framework for understanding these trade-offs and selecting appropriate consensus mechanisms for specific application contexts. Finally, we discussed future development trends, as well as regulatory and ethical considerations.
Md. Rafid Haque, Sakibul Islam Munna, Sabbir Ahmed, Md. Tariqul Islam · 6 authors
Centralized version control systems (VCS) are vital for software development but pose risks of data loss and ownership disputes. While blockchain offers a decentralized alternative, existing solutions are often hindered by high latency, compromising the real-time collaboration essential for modern workflows. This study introduces a novel hybrid architecture combining the security of the Ethereum blockchain and the InterPlanetary File System (IPFS) with two key contributions: 1) Shamir's Secret Sharing (SSS) to create a trust-minimized model for key distribution, and 2) an authoritative-first, optimistic-fallback retrieval protocol utilizing a temporary middleware to decouple the user experience from blockchain confirmation delays. We implemented a full prototype and conducted a comprehensive performance evaluation on the public Sepolia testnet. Our results demonstrate that this architecture not only provides a secure, auditable, and resilient platform for source code hosting but also achieves highly competitive user-perceived performance. Our user-perceived push time reduces submission latency by up to 49% compared to a standard git push for common repository sizes, proving that a well-designed decentralized VCS can balance the core tenets of security and decentralization with the practical need for speed and efficiency.
Gas fees play a crucial role in Ethereum blockchain transactions, directly affecting the cost and efficiency of decentralized applications. This study analyzes gas fee patterns across transaction types, temporal trends, and anomalous behaviors using a dataset of 1,000 Ethereum transactions. The results reveal that the average gas price was 120.5 Gwei, with a standard deviation of 45.2 Gwei, highlighting significant variability. Smart contract functions exhibited varying gas usage, with mint operations consuming the highest average gas (1,500,000 units) compared to approve (1,200,000 units) and transfer (800,000 units). A positive correlation (r = 0.65) was observed between gas price and value transferred, suggesting that higher-value transactions often incur elevated gas fees. Temporal analysis showed predictable patterns, with peak gas prices occurring between 13:00 - 17:00 UTC during high network activity and lower prices between 02:00 - 06:00 UTC. Additionally, anomaly detection identified 15 outlier transactions, including one with an unusually high gas price of 500 Gwei, reflecting network congestion or prioritization strategies. These findings provide actionable insights for optimizing transaction costs and improving smart contract efficiency. Future research could explore layer-2 scaling solutions, alternative fee mechanisms, and machine learning approaches for gas price prediction. This study contributes to a deeper understanding of Ethereum’s gas fee dynamics, offering valuable guidance for developers, users, and researchers in the blockchain ecosystem.