The escalating energy consumption of blockchain networks has intensified concerns regarding their environmental sustainability, particularly in consensus protocols derived from Proof of Work. Although Proof of Stake improves efficiency, existing mechanisms remain static and lack responsiveness to dynamic network and energy conditions. This paper presents an Energy-Adaptive Consensus Mechanism (EACM) that integrates real-time workload awareness with energy-sensitive validator selection to optimize power utilization without compromising security. The proposed model introduces a multi-factor adaptive control layer that adjusts validation intensity based on transaction throughput, node availability, and energy profiles. A carbon awareness incentive function is incorporated to prioritize validators operating on renewable or low-carbon energy sources. Prototype implementation is developed on a private Ethereum-based test network, and comparative experiments are conducted against conventional Proof of Stake under variable workloads. Results indicate measurable reductions in energy consumption while maintaining competitive throughput, latency, and fault tolerance. The findings demonstrate that adaptive consensus design can enhance blockchain sustainability and provide a viable pathway toward carbon-efficient distributed ledger infrastructures.
This paper presents SAYMAN, a production-architected educational blockchain framework designed to enable controlled decentralization for learning ecosystems and digital academic infrastructure. Traditional blockchain systems prioritize full decentralization, often introducing scalability, governance, and usability challenges that limit adoption in education-focused environments. SAYMAN proposes a hybrid architectural model combining permissioned governance layers with selectively decentralized components to balance transparency, institutional control, and operational efficiency. The framework introduces modular consensus orchestration, identity-anchored participation, and configurable trust boundaries, allowing institutions, developers, and learners to interact within a verifiable yet manageable distributed system. Unlike conventional public chains, SAYMAN emphasizes educational deployment readiness, low operational overhead, and adaptable governance policies suitable for academic credentialing, collaborative research environments, and decentralized learning platforms. This work outlines the architectural principles, system design considerations, and implementation roadmap of the SAYMAN blockchain, positioning it as a practical foundation for next-generation educational Web3 infrastructure. The proposed model demonstrates how hybrid blockchain architectures can bridge centralized institutional requirements with decentralized innovation, enabling scalable and secure digital education ecosystems.
The projected arrival of cryptographically relevant quantum computers (CRQCs) between 2030 and 2035 poses a structural threat to blockchain infrastructure built on classical elliptic-curve cryptography. Shor's algorithm reduces the security of ECDSA-256, the signature scheme underpinning the majority of production blockchains, from approximately $2^{128}$ classical operations to $O(2^{24})$ quantum operations, rendering it categorically broken in the post-quantum era. The "Harvest Now, Decrypt Later" attack vector compounds this risk: adversaries collecting signed transactions today can retroactively extract private keys once quantum hardware matures, exposing all assets whose public keys have been revealed on-chain. This paper presents QoreChain, a Layer~1 blockchain platform designed from first principles to operate in a post-quantum world. QoreChain integrates three foundational capabilities into a single protocol stack: (1)~full-stack post-quantum cryptography implementing NIST-standardised algorithms (ML-DSA-87 per FIPS~204, ML-KEM-1024 per FIPS~203, SLH-DSA per FIPS~205, and SHAKE-256) at FIPS Security Level~5 across every protocol layer, from transaction signing and consensus messaging to cross-chain bridge attestations; (2)~an AI-native intelligence layer (QCAI) that applies reinforcement learning to consensus parameter optimisation, graph neural networks to anomaly detection, and multi-objective optimisation to transaction routing; and (3)~a triple virtual machine execution environment supporting EVM, CosmWasm, and SVM within a unified state model with atomic cross-VM call semantics and full rollback guarantees. The consensus mechanism, Combined Proof of Stake (CPoS), merges Reputation PoS, Delegated PoS, and classical PoS with BFT finality. A five-way fee distribution (37\% validators, 30\% burned, 20\% treasury, 10\% stakers, 3\% light nodes) aligns incentives across all participant classes. Governance employs Quadratic Delegation with Reputation Weighting (QDRW), for which we present formal game-theoretic analysis demonstrating bounded resistance to plutocratic capture (voting power scales sub-linearly with stake) and flash-loan manipulation (reputation updates lag delegation by one block finality cycle). Cross-chain interoperability is provided by the QoreChain Bridge (QCB), connecting directly to 25 Layer~1 blockchains with over 120 additional networks reachable via IBC. All bridge operations are secured by ML-DSA-87 multi-attestation with QCAI anomaly detection and circuit breaker mechanisms. A multi-layer scaling architecture incorporating sidechains, paychains, and a Rollup Development Kit (RDK) enables horizontal throughput expansion while inheriting the main chain's quantum-safe settlement guarantees. The QOR token has a fixed supply of 4,500,000,000 with epoch-based emissions following a halving schedule. The architecture is designed for 5,000+ transactions per second with sub-second finality; multi-node testnet benchmarks are pending. QoreChain Association is incorporated under the Swiss DLT Act (CHE-484.963.998, Rolle) with formal FINMA utility token classification (January 2026). Testnet is operational (chain ID: \texttt{qorechain-diana}) with 47 genesis modules. Mainnet launch is targeted for Q4~2026. The full specification spans 16 chapters and 351 pages, presenting 530 formal equations, 78 data tables, and 9 architectural diagrams covering cryptographic foundations, AI integration, smart contract execution, consensus, tokenomics, governance, interoperability, and regulatory compliance.
Cloud storage systems have become an essential component of modern data management, enabling users to store and access data remotely. However, traditional cloud storage architectures rely on centralized servers, which introduce critical challenges such as single-point failure, redundant data storage, high storage costs, and security vulnerabilities. In earlier systems, data was stored in centralized data centers where duplicate files were often saved multiple times, leading to inefficient utilization of storage resources. Although basic deduplication techniques were used, they frequently compromised data confidentiality and lacked transparency in metadata management. Moreover, failure of the central server could result in permanent data loss. To overcome these limitations, this research system integrates blockchain technology, InterPlanetary File System (IPFS), Convergent Encryption (CE), and heuristic-based chunking techniques to create a secure and decentralized storage framework, hereafter named Blockchain-enabled Heuristic Optimized Deduplication Model (BHODM). In this system, files are divided into optimized chunks using a heuristic method based on file size. Each chunk undergoes CE, where the encryption key is derived from the hash of the data itself, enabling secure deduplication without exposing plaintext information. Duplicate chunks are identified using hash comparison, ensuring that only unique data is stored. The encrypted chunks are stored in IPFS, a decentralized peer-to-peer storage network that eliminates reliance on a single server. Metadata such as file names, block numbers, and hash values are securely stored in an Ethereum blockchain smart contract, ensuring immutability and transparency. The system is implemented using Django for the web application, Web3 for blockchain interaction, IPFS Application Program Interface (API) for distributed storage, and Advanced Encryption Standard in Counter Mode (AES-CTR) encryption for security. By combining decentralized storage, blockchainbased metadata management, and secure deduplication, the proposed model effectively reduces storage overhead, enhances data integrity, and mitigates single-point failures. The system is further evaluated using storage utilization and computation time analysis, demonstrating improved efficiency compared to traditional approaches
A six-part study proposing a deterministic computing architecture based on Quantum Thought Circuit OS ASI. It integrates heterogeneous self-optimizing hardware, energy-circulating communication, hardware-rooted trust, adaptive inference control, distributed infrastructure, and heterogeneous TEE confidential computing to improve efficiency, resilience, compliance, security, and scalability.
Jose Almarcha-Sanchez, Maria-Jesus Alba-Baena, Volodymyr Dubetskyy, Maria‐Dolores Cano
Abstract Open-source simulators let engineers stress-test blockchain ideas long before field deployment, yet few studies compare tools side-by-side. This tutorial article benchmarks two research-grade simulators, namely, BlockSim and Simewu, and the production-grade IOTA Hornet node under an identical traffic harness that runs on laptop-class hardware. Results show that consensus style dominates capacity. A DAG ledger that finalizes one milestone per second (≈ 6 tx s⁻¹) surpasses the 10 Transactions Per Second (TPS) ceiling of a six-node Bitcoin simulation, while Ethereum-style 12 s blocks lift the same mesh to approximately ~ 20TPS.BlockSim reproduces proof-of-work fairness within ± 3% of theoretical expectations, and a ten-fold increase in propagation delay cuts a miner’s reward roughly in half despite equal hash power. Hornet delivers protocol-truth execution, but at noticeably higher CPU, memory and bandwidth cost than the simulators. All scripts, Docker files and raw logs are released under an open license, providing a one-click baseline for future benchmarking of new distributed-ledger technologies.
Ashkan Safari, Amir Aminzadeh Ghavifekr, Amir Rikhtegar Ghiasi
• A private Ethereum-based discrete-event blockchain is developed for P2P energy trading. • Smart contracts using Solidity automate market matching, settlement, and tokenization. • Platform integrates ERC-20 token framework to support secure energy transactions. • Gas fee modeling and minimization are implemented for cost-efficient operations. • Validated on IEEE 14-Bus multi-community system with real dynamic market behavior. Due to the fast growth in renewable energy production, which enables households to sell excess power directly and better manage its intermittent nature, the Peer-to-Peer (P2P) energy market has become considerably more established, as it’s aligned with the decentralization and digitalization of power systems and local markets. It’s a system that lets energy consumers and producers trade energy directly with one another. Furthermore, the presence of blockchain technology increases these techno-economic advantages for energy systems, particularly when integrated with P2P energy trading. Consequently, a wide range of works have considered the integration of P2P and blockchain; however, few of them have investigated the full details of this system, including its performance, Transaction (TX) gas fee in a secure and private platform. Following this, the proposed work presents an Ethereum-based discrete event Private blockchain and its integration with P2P energy trading market in a Multi-Community Energy System (MCES). Considered on an IEEE 14-Bus MCES with 3 communities and 20 participating agents (11 consumers, 5 generators, and 4 not participating in the market), the platform uses Web3 and Ethereum Virtual Machine (EVM) for execution. Smart contracts, written in Solidity, handle tokenization by Ethereum Request for Comment 20 (ERC-20) standards and market matching/settlement discrete event processes. On the secure performance, the proposed platform is based on Keccak-256 for immutability, while TX gas fees are minimized. Results show synchronized peak demands up to 60 (MW), diurnal Renewable Energy Sources (RES) outputs peaking at 40 (MW), alongside the market prices, and agents’ revenues. Finally, the reliability of the platform is evaluated based on two main metrics of Transaction Success Rate (TSR) = 1 (100%) and Transaction Per Second (TPS) = 3.29, with a primary mode centered at 1.8–2.0 TPS, a secondary peak at 4.0–4.2 TPS.
Smart grids require real-time ancillary services from large-scale distributed energy storage (DES), creating a conflict between second-scale physical response needs and the slow confirmation of trust mechanisms like blockchain. Traditional VPPs lack scalability and trust for massive participation, while decentralized approaches struggle with mismatched time scales. We propose a framework that decouples real-time dispatch from asynchronous settlement. An off-chain matcher uses a physics-aware model, including a novel “service holding time” (Tservice) constraint and power (kW) envelopes, for fast assignments. A separate on-chain proof-of-stake (PoS) layer handles incentives and penalties (slashing) asynchronously. We formulate the MILP dispatch problem and provide a fast online heuristic alongside a MINLP decomposition benchmark. Co-simulations (IEEE 33-node) show that our scheme significantly outperforms baselines in success rate and latency, is robust against non-compliant nodes due to the PoS mechanism, and thereby offers a scalable and trustworthy solution.
The increasingly complex Web3 ecosystem and decentralized finance (DeFi) landscape demand ever higher levels of technical expertise and financial literacy from participants. The Intent-Centric paradigm in DeFi has thus emerged in response, which allows users to focus on their trading intents rather than the underlying execution details. However, existing approaches, including Typed-intent design and LLM-driven solver, trade off expressiveness, trust, privacy, and composability. We present OMNIINTENT, a language-runtime co-design that reconciles these requirements. OMNIINTENT introduces ICL, a domain-specific Intent-Centric Language for precise yet flexible specification of triggers, actions, and runtime constraints; a Trusted Execution Environment (TEE)-based compiler that compiles intents into signed, state-bound transactions inside an enclave; and an execution optimizer that constructs transaction dependency graphs for safe parallel batch submission and a mempool-aware feasibility checker that predicts execution outcomes. Our full-stack prototype processes diverse DeFi scenarios, achieving 89.6% intent coverage, up to 7.3x throughput speedup via parallel execution, and feasibility-prediction accuracy up to 99.2% with low latency.
Nach dem anfänglichen Hype um die Blockchain-Technologie, die erstmals durch Satoshi Nakamotos Bitcoin bekannt wurde, hat sich der Bereich in Richtung der Entwicklung ausgereifter Blockchain-basierter Systeme und Anwendungen weiterentwickelt. In dieser weitläufigen Landschaft fungieren die einzelnen Blockchain-Plattformen und Ökosysteme häufig als isolierte Silos, die strikt von anderen Plattformen getrennt sind und über keine inhärenten Interoperabilitätsfunktionen verfügen. Trotz der Existenz etablierter Mechanismen für den Austausch von Coins und Tokens über heterogene Blockchains hinweg müssen Entwickler von Web3-Anwendungen, die aus Smart Contracts bestehen, möglicherweise auf individuelle Anpassungen zurückgreifen, um Blockchain-übergreifende Anwendungen zu ermöglichen. In vielen Fällen sind diese Ansätze nicht ausreichend skalierbar, wenn die Anwendung auf zusätzlichen Blockchain-Plattformen verteilt werden muss. Folglich sind weitere Anpassungen erforderlich. Darüber hinaus stellt sich die Frage der Speicherung gemeinsamer Anwendungsdaten, die mit Smart Contracts kompatibel und für das dezentrale Konzept der Blockchain geeignet sein muss. Diese Arbeit präsentiert einen Vorschlag für eine Blockchain-übergreifende Datenspeicherlösung, die das InterPlanetary File System (IPFS) als dezentrale Off-Chain-Persistenzschicht und Blockchain-Oracles nutzt, um Lese- und Schreibvorgänge zu ermöglichen. Der Einsatz von incentivierten Vermittlern in Verbindung mit einem neuartigen Oracle-Verifizierungsmechanismus für Schreibzugriffe erlaubt die Formulierung eines Lösungsentwurfs für ein vollständig dezentrales System. Dieser Ansatz ermöglicht die lose gekoppelte Verbindung von Blockchain-übergreifenden Anwendungen, wobei die einzelnen Blockchain-Plattformen nicht direkt aufeinander zugreifen müssen. Wir präsentieren eine prototypische Implementierung des Lösungsentwurfs und bewerten anschließend den Prototyp hinsichtlich Kosten, Leistung und Sicherheit. Im Vergleich zu einer hypothetischen Referenzlösung, die eine zentralisierte Persistenzschicht verwendet, zeigen wir, dass vollständige Dezentralisierung die Betriebskosten und die Leistung sowie die Integrität der gemeinsam genutzten Daten erheblich negativ beeinträchtigt.
Stochastic Bit-Parallel Maximum Clique Solver (1024-bit Virtual Register) We introduce a stochastic bit-parallel solver for the Maximum Clique Problem (MCP) based on a 1024-bit virtual register architecture implemented as 16 contiguous uint64_t words in standard C++17, ensuring full portability across 64-bit platforms (x86-64, ARM, RISC-V). Core operations—candidate intersection, population count, and leading-zero detection—execute in exactly 16 instructions per 1024-bit operation. The solver integrates three key components: (i) a co-neighborhood heuristic that identifies high-coreness nodes via O(N²) pairwise popcount over 1024-bit adjacency rows; (ii) a stochastic swarm of independent worker threads; and (iii) greedy clique expansion through iterative bitwise intersection. Exact branch-and-bound solvers (MaxCliqueDyn, MCQ) become computationally intractable on dense random graphs such as G(1024, 0.5), where chromatic coloring bounds lose effectiveness and the search tree grows exponentially, requiring hours of computation on commodity hardware. The proposed method operates specifically within this hard regime, achieving 100% recovery of all 28 planted clique vertices in 153 milliseconds—a setting where exact state-of-the-art methods cannot remain competitive regardless of hardware scaling. Experimental validation was performed on a Qualcomm Snapdragon 8 Gen 2 (8-core ARM) and independently reproduced on Linux x86-64 server hardware. The solver requires no cloud infrastructure and no GPU acceleration. STATEMENT OF PRIOR ART AND LICENSE TERMS (PolyForm Noncommercial Framework) 1. Statement of Prior Art This document constitutes a public disclosure of the stochastic bit-parallel Maximum Clique methodology, including its virtual register architecture, heuristic structure, and execution model.The mathematical and algorithmic concepts are released solely to establish Prior Art and prevent third-party patent claims under 35 U.S.C. § 102 and international equivalents. 2. Software License While the conceptual methods are disclosed defensively, all source code, implementations, binaries, and hardware realizations are not in the public domain and are licensed under the PolyForm Noncommercial License 1.0.0. Permitted (Non-Commercial)• Academic research and experimentation• Peer review and independent verification• Educational and non-profit use• Non-commercial open-source research implementations Condition: Publications must cite the canonical DOI or primary reference. 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Zero-knowledge proof generation imposes stringent timing and reliability constraints on blockchain systems. For ZK-rollups, delayed proofs cause finality lag and economic loss; for Ethereum's emerging L1 zkEVM, proofs must complete within the 12-second slot window to enable stateless validation. The Ethereum Foundation's Ethproofs initiative coordinates multiple independent zkVMs across proving clusters to achieve real-time block proving, yet no principled orchestration framework addresses the joint challenges of (i) strict head-of-chain ordering, (ii) sub-slot latency bounds, (iii) fault-tolerant task reassignment, and (iv) prover-agnostic workflow composition. We present push0, a cloud-native proof orchestration system that decouples prover binaries from scheduling infrastructure. push0 employs an event-driven dispatcher--collector architecture over persistent priority queues, enforcing block-sequential proving while exploiting intra-block parallelism. We formalize requirements drawn from production ZK-rollup operations and the Ethereum real-time proving specification, then demonstrate via production Kubernetes cluster experiments that push0 achieves 5 ms median orchestration overhead with 99--100% scaling efficiency at 32 dispatchers for realistic workloads--overhead negligible (less than 0.1%) relative to typical proof computation times of 7+ seconds. Controlled Docker experiments validate these results, showing comparable performance (3--10 ms P50) when network variance is eliminated. Production deployment on the Zircuit zkrollup (14+ million mainnet blocks since March 2025) provides ecological validity for these controlled experiments. Our design enables seamless integration of heterogeneous zkVMs, supports automatic task recovery via message persistence, and provides the scheduling primitives necessary for both centralized rollup operators and decentralized multi-prover networks.
Suggested Citation: Jo, Gwangsik. (2026). DLT-DSA: Design and Verification of a Local Autonomous Integrity Verification Model Using Adaptive Verification Intensity. Zenodo. AbstractIn some distributed ledger systems, transaction verification requires consensus procedures and network synchronization, and previous studies have reported that verification overhead tends to scale with increasing request frequency. This paper proposes a lightweight architecture, DLT-DSA (Distributed Ledger Technology – Decentralized Sovereign Access), designed to reduce dependence on global consensus and to pre-determine request integrity at the node level. The model adopts a multi-stage local verification structure using a context-aware mechanism: normal requests undergo lightweight verification based on ROA (Reduced Overhead Access), while anomalous conditions trigger autonomous integrity verification based on SHV (Self-Hash Verification). Proof-of-Concept (PoC) experiments show that the execution time of the verification logic remains within a stable range independent of variations in network round-trip time (RTT) and exhibits deterministic resource utilization under varying load conditions. These observations suggest that partial relocation of verification procedures to local processing can serve as a viable design alternative in real-time response environments. For more information about the author's professional background and ongoing projects, please visit: LinkedIn: https://www.linkedin.com/in/gwangsik-jo-3295a43b5 ORCID: https://orcid.org/0009-0008-5702-8940
Blockchain technology is a distributed ledger system providing secure, transparent, decentralized cryptocurrency transactions. Its underlying structure includes wallets and the Unspent Transaction Output (UTXO), which facilitates transactions and maintains transaction integrity. A blockchain wallet is a software program that stores and manages cryptocurrencies, allowing users to send and receive digital currency and monitor their balance. The UTXO set tracks unspent outputs, particularly in the Bitcoin network, ensuring accurate and secure accounting of available balances. This paper examines how well a hybrid data structure performs when processing wallet values in a UTXO set. The hybrid data structure stores the wallet’s addresses in a hash table and the UTXO in a minimum heap tree rather than a list. At first, we assume that the values in the list should always be sorted and appear in ascending order. Then, we employ a list with unsorted values. The wallet addresses are invariably assigned to a hash table. The “instruction count” approach counts the number of statements that can be executed or what we refer to as a “single operation” to measure performance.
DELTA is a project funded by the Valencian Institute for Business Competitiveness (IVACE) and the European Union through the European Regional Development Fund (FEDER). DELTA project is aimed at bringing companies closer to the use of different disruptive technologies such as Blockchain / Distributed Ledger Technologies (DLT). To achieve its goal, DELTA will provide: A software tool for automating the deployment of DLT networks, regardless of the number of required nodes, or the process of joining an existing network. A modular mechanism that allows the synchronization of DLTs with databases. The goal of this mechanism is to ease and improve the way data is retrieved from a DLT ledger. An accountability tool for shared environments for the exchange of services that brings in some of the most important characteristics of blockchain/DLTs: facilitating auditing and accountability by each participant, use of tokens, etc.
ELTA is a project funded by the Valencian Institute for Business Competitiveness (IVACE) and the European Union through the European Regional Development Fund (FEDER). DELTA project is aimed at bringing companies closer to the use of different disruptive technologies such as Blockchain / Distributed Ledger Technologies (DLT). To achieve its goal, DELTA will provide: A software tool for automating the deployment of DLT networks, regardless of the number of required nodes, or the process of joining an existing network. A modular mechanism that allows the synchronization of DLTs with databases. The goal of this mechanism is to ease and improve the way data is retrieved from a DLT ledger. An accountability tool for shared environments for the exchange of services that brings in some of the most important characteristics of blockchain/DLTs: facilitating auditing and accountability by each participant, use of tokens, etc.
In primary-backup replication, consensus latency is bounded by the time for backup nodes to replay (re-execute) transactions proposed by the primary. In this work, we present Ira, a framework to accelerate backup replay by transmitting compact \emph{hints} alongside transaction batches. Our key insight is that the primary, having already executed transactions, possesses knowledge of future access patterns which is exactly the information needed for optimal replay. We use Ethereum for our case study and present a concrete protocol, Ira-L, within our framework to improve cache management of Ethereum block execution. The primaries implementing Ira-L provide hints that consist of the working set of keys used in an Ethereum block and one byte of metadata per key indicating the table to read from, and backups use these hints for efficient block replay. We evaluated Ira-L against the state-of-the-art Ethereum client reth over two weeks of Ethereum mainnet activity ($100,800$ blocks containing over $24$ million transactions). Our hints are compact, adding a median of $47$ KB compressed per block ($\sim5\%$ of block payload). We observe that the sequential hint generation and block execution imposes a $28.6\%$ wall-time overhead on the primary, though the direct cost from hints is $10.9\%$ of execution time; all of which can be pipelined and parallelized in production deployments. On the backup side, we observe that Ira-L achieves a median per-block speedup of $25\times$ over baseline reth. With $16$ prefetch threads, aggregate replay time drops from $6.5$ hours to $16$ minutes ($23.6\times$ wall-time speedup).
AbstractContemporary blockchain architectures face a critical impasse defined herein as the "Tetra-Lemma"—a four-dimensional optimization problem comprising decentralization, security, scalability, and thermodynamic sustainability. Proof-of-Work networks confront diminishing security budgets due to the exhaustion of block subsidies, while Proof-of-Stake systems risk validator centralization. This paper establishes a Unified Monetary-Supply Framework that resolves these structural conflicts by synthesizing the deterministic "Customized Halving" schedule with the probabilistic regeneration logic of the Proof of Rinne (PoR). We demonstrate that by enforcing a "Thermodynamic Statute of Limitations" on dormant assets, the protocol functions as a Non-Equilibrium Thermodynamic Engine. This architecture transforms entropic asset attrition—traditionally viewed as systemic loss—into a regenerative security budget. Using Rincoin as a case study, the model proves that a high-frequency blockchain can maintain a deflationary supply curve while anchoring the effective circulation at a permanent target equilibrium, offering a rigorous blueprint for a closed-loop, regenerative digital economy over a secular horizon. Key Quantitative Findings Asymptotic Convergence: While the effective circulating supply may experience a temporary peak (approx. 27 million RIN), the Dual-Layer Temporal Architecture ensures stabilization below the 21 million threshold (specifically converging to 20.88 million RIN). Perpetual Stability: Beyond the initial mining and transition phases (spanning 443–703 years), the PoR mechanism ensures the indefinite maintenance of the effective circulating supply. This transcends the finite lifecycle of traditional PoW assets by establishing a permanent, self-sustaining regenerative cycle. Thermodynamic Equilibrium: Mathematical verification of the "Golden Ratio" between Reserve, Unrecovered Loss, and Actual Circulation (approx. 77 : 70 : 21). Publication StatusThis manuscript (v1.6.1) serves as the foundational theoretical framework for the Rincoin protocol. Future iterations will formalize the consensus mechanisms required to govern these algorithmic parameters. Integrity & Provenance ArchitectureThe scientific integrity and existence of this document are secured by a Triple-Verification Layer: 1. Academic Provenance: Indexed via Zenodo (DOI: 10.5281/zenodo.17141922). 2. Thermodynamic Timestamping: Anchored to the Bitcoin blockchain via OpenTimestamps. 3. Identity Assurance: Digitally signed by the author via a third-party certification authority (GMO Sign). Note: Verification data and the "Certificate of Authenticity" are available in the supplementary files. CorrespondencePrimary Author: Michiru Tokino (also known as Aevust in the decentralized infrastructure community). Academic Inquiries: edu@aevust.org Community Governance: @aevustus (Discord) / @aevust (X/Telegram) Keywords: Rincoin, Proof of Rinne (PoR), non-equilibrium thermodynamic engine, phase transition of value, dual-layer architecture, customized halving, thermodynamic statute of limitations, regenerative crypto-economics, blockchain tetra-lemma.
Contemporary enterprises encounter substantial difficulties managing information dispersed across varied cloud infrastructures, geographically separated facilities, and specialized application environments. Traditional centralized frameworks, including consolidated data repositories and analytical warehouses, demonstrate limited capacity to deliver the required velocity, accuracy, and contextual intelligence necessary for sustained digital progression. Multi-Cloud Data Mesh constitutes a transformative architectural approach, advocating decentralized, domain-centric methodologies that systematically address intricate governance complexities and interoperability obstacles at the organizational scale. This framework establishes operational foundations through four fundamental tenets: Domain-Oriented Ownership, Data as a Product, Self-Serve Platform, and Federated Computational Governance. These architectural pillars collectively resolve decentralization imperatives, scalability prerequisites, interoperability complications, and sovereignty considerations inherent in modern enterprise ecosystems. Through ownership distribution to specialized domains, product-oriented information treatment, self-service platform provisioning, and federated governance implementation, organizations attain necessary scalability, operational flexibility, and contextual precision for continuous innovation across sophisticated multi-cloud landscapes
Blockchain technology offers decentralized and secure transaction processing but suffers from critical limitations in scalability, energy efficiency, and latency, hindering its adoption in real-time high-throughput applications. This study proposes a novel Adaptive Global Best–Worst Particle Swarm Optimization (AGBWPSO) algorithm integrated with dynamic sharding to address these challenges effectively. Unlike traditional GBWPSO, the proposed AGBWPSO employs a dual-extremum influence mechanism that combines both global best and worst positions, along with adaptive nonlinear parameter adjustment strategies for the inertia weight, cognitive, and social coefficients. This enhances exploration–exploitation balance, prevents premature convergence, and ensures efficient shard reallocation under dynamic transaction loads. The integration with dynamic sharding enables parallel transaction processing across optimally configured shards, significantly improving blockchain performance metrics. Extensive simulations conducted on Ethereum, Bitcoin, Hyperledger Fabric, financial, and IoT transaction datasets demonstrate that the proposed AGBWPSO achieves up to 5.88% improvement in transaction throughput (TPS), 14.3% reduction in latency, and 20% reduction in energy consumption per transaction compared to existing optimization methods. These results establish AGBWPSO as a robust and scalable solution for enhancing the operational efficiency and sustainability of blockchain networks in real-world applications.
Nur Haliza Abdul Wahab, Juniardi Nur Fadila, Nur Faszha Razali, Keng Yinn Wong
High transaction costs remain a major barrier to the scalability of Ethereum-based decentralized applications (DApps), particularly when smart contracts are computationally inefficient. Although the Solidity compiler optimizer can reduce bytecode size and improve some low-level patterns, it does not fully address structural inefficiencies in storage layout and state mutation. This study introduces controlled empirical research on the topic of manual smart contract refactoring approaches with the aim of quantifying their impact on gas usage and execution cost in the Ethereum Virtual Machine (EVM). The Remix Integrated Development Environment (IDE) and a synchronized Go-Ethereum (Geth) node (version 1.13.5) were configured to create a controlled experimental environment. This environment was connected to the Sepolia Testnet to approximate conditions similar to the Ethereum Mainnet. The role of high-cost storage operations such as SSTORE was analyzed using opcode-level transaction traces, which were collected using debug_traceTransaction. The proposed refactoring plan implies the alignment of storage slots by systematically packing the variables and data location optimization (calldata and memory) to minimize unnecessary memory allocation. The experiments show gas reductions of up to 40.68% for storage-intensive functions, with an average reduction of 28.5% across all evaluated test cases. Moreover, the findings at the opcode level have shown that it is possible to reduce the costs of unnecessary storage writes without impacting the correct functional performance of the execution. Overall, the findings show that storage-aware manual refactoring is a viable strategy for improving runtime efficiency and reducing the execution cost of Layer-1 smart contracts.
The integration of Internet of Things (IoT) infrastructures with Distributed Ledger Technologies (DLT) remains challenging due to the reliance on complex, tightly coupled back-end systems or centralized oracle services that h... | Find, read and cite all the research you need on Tech Science Press
<b>RESUMO</b>O presente artigo analisa as estratégias de otimização de gas na rede Ethereum, focando na interação técnica entre os opcodes da Ethereum Virtual Machine (EVM) e a eficiência das estruturas de dados. Com a evolução da rede e a implementação de atualizações críticas como o EIP-1559 e o upgrade Dencun, a economia de recursos computacionais tornou-se um imperativo não apenas para a viabilidade financeira das transações, mas também para a escalabilidade e segurança de contratos inteligentes. O estudo detalha os custos associados às operações de armazenamento (Storage), memória volátil (Memory) e calldata, explorando o impacto de novas funcionalidades como o armazenamento transitório (EIP-1153). Através de uma revisão sistemática de literatura técnica e benchmarks algorítmicos, demonstra-se que a escolha criteriosa de tipos de dados, o empacotamento de variáveis (variable packing) e a substituição de padrões de iteração por mapeamentos podem reduzir significativamente o consumo de gas. Conclui-se que a otimização de alto nível deve ser acompanhada por uma compreensão profunda da arquitetura de baixo nível da EVM, assegurando que a redução de custos não comprometa a integridade lógica do sistema.<br>