Aplicações computacionais de bases de dados distribuídas estão sempre presentes na sociedade digital. Uma importante questão é que essas bases de dados sejam seguras, auditáveis, transparentes e escaláveis. Este artigo possui dois objetivos: (i) prover um arcabouço teórico sobre Distributed Ledger Technologies (DLTs) para implementação de bases de dados distribuídas, e (ii) propor um método de seleção do tipo de plataforma DLT para uma organização alvo, denominado Método Ágil de Seleção (MAS). Para tanto, inicialmente realizamos um estudo de trabalhos da literatura e, na sequência, derivamos o MAS. Além disso, demonstramos a aplicabilidade do MAS por meio de um estudo de caso. Por fim, conclusões gerais e trabalhos futuros encerram este artigo.
Web3 has received considerable attention from industry and academia due to its groundbreaking revolution to decentralize the current centralized web. As a fundamental building block, blockchain provides web3 with the ability to rebuild trust in the trustless decentralized web. More and more blockchain-based web3 applications are taking place and becoming successful. Many web3 applications generate coupled data and transactions from multiple blockchains and demand efficient and atomic cross-blockchain transaction processing; however, existing approaches rarely consider transaction atomicity, and the processing efficiency is inferior. In this work, we formally model multi-blockchain systems and formulate the cross-blockchain transaction processing problem. Then, we propose a novel consensus mechanism, namely proof of credible contributions, to solve the efficiency and atomicity issues in cross-blockchain transaction processing. Inside, we define credible contributions as a measure of blockchain nodes’ credits and workload, so as to make nodes compete to handle as many cross-blockchain transactions as possible. Furthermore, we propose the flag-referenceconfirm protocol to guarantee transaction atomicity. Extensive experimental results indicate the efficiency and effectiveness of proof of credible contributions.
This study explores the integration of Plithogenic Hypersoft Sets (PHSS) in Multi-Criteria Decision Making (MCDM) for cryptocurrency investment analysis. Given the volatile and unpredictable nature of the cryptocurrency market, traditional decision-making models often fail to capture the complexities and uncertainties present. By incorporating the advanced concept of PHSS, which accommodates multiple membership degrees (fuzzy, intuitionistic fuzzy, neutrosophic), we propose a more robust framework for investment decision-making. The study normalizes cryptocurrency data and applies PHSS to a set of cryptocurrencies (e.g., BTC, ETH, BNB, SOL, and XRP), analyzing key attributes such as price changes, market cap, volume, and circulating supply. Our results demonstrate that PHSS can enhance the accuracy and reliability of financial decision-making, providing valuable insights for investors.
R. Revathi, Kamal Sharma, Gundavarapu Mallikarjuna Rao, Ammar Hameed Shnain · 6 authors
Although DeFi has been presented as the new generation of financial systems that cuts across all centralized financial systems, it is an innovation based on blockchain technology, which establishes global and open financial platforms of decentralized permissionless finance. Nonetheless, DeFi ecosystems have high levels of fragmentation, which creates difficulties for the unification of different protocols and blockchains to cooperate and communicate with each other. Subsequently, Graph Neural Networks (GNNs) have garnered considerable attention as a promising approach to model feature-interaction and extract insights from graph-structured data. In this paper, we introduce the Interoperable GNN DeFi Framework, which adapts the use of GNNs to work as a solution to the interoperability concern in Defi ecosystems. The following are the main components of the proposed system: graph representation, data integration, GNN model, interface and interoperability, monitoring and messaging, scalability optimization, and security considerations. Under the mentioned framework, positive results are notable for several scopes of interoperability, such as cross-chain operations with tokens, compatibility with other protocols, provision of liquidity, and risk tackling. The results shown below explain how much the efficiency, expandability, durability, and accessibility in the decentralized finance could be improved while using the GNN-based approaches. Future work in this topic entails the progression of the prior areas of research such as scalability, dynamics modeling, interdisciplinary collaboration, standardization, and security focusing on the continuing enhancement of interoperability opportunities in decentralized finance.
M. Arun, P. Gururama Senthilvel, A. Muthukrishnan, N. Poongavanam · 5 authors
This research proposes a blockchain based Distributed Resource Management and Allocation (DRMA) system for the Cloud Computing environment to overcome the shortcomings, ill prepared security and high cost incurred by the CC based on centralized and monolithic cloud architecture. The proposed system takes advantage of blockchain systems since they are distributed and due to their capability of not being altered once implemented, smart contracts are used to facilitate the distribution of resources. Moreover, the application of the Proof-of-Stake consensus mechanism and dynamic algorithms to distribute resources and prevent resource monopolization allow obtaining a high level of resource utilization together with low fees and high security levels. The implementation utilizes Ethereum’s blockchain and evaluate real-world cloud environments’ efficiency for resource utilization, transaction throughput, cost and robustness. This paper examines how blockchain has the propensity to redesign the means through which cloud computing resource management while improving its security, efficiency, and scalability.
Calebe P. Bianchini, Geraldo Lucas Fernandes do Amaral, Danilo Bizarria de Oliveira
Sistemas de processamento de transações são parte essencial de negócios online, e exigem tanto confiança quanto desempenho para entregar o serviço esperado. Uma ferramenta de blockchain é capaz de oferecer escalabilidade e confiança na validação de transações. A abordagem proposta neste trabalho é da avaliação do potencial de escalabilidade da rede Ethereum, e seu comportamento em cenários progressivamente mais distribuídos. Para tal, foram coletadas métricas de throughput e latência por meio da execução de redes em cinco diferentes escalas (de 1 a 16 nós, em progressão geométrica de razão 2). Destacam-se duas variações cuja significância estatística foi testada pelo Teste U de Mann-Whitney: um aumento de até dez vezes o número de transações por segundo, quando comparados um nó isolado e uma rede de 16 nós, e uma queda de até metade da latência com relação ao cenário centralizado. Os ambientes de testes foram escolhidos para tentar representar um ambiente com usuários reais.
Maryam Fattahi Vanani, Hamidreza Shayegh Borujeni, Ali Nourollah
Blockchain has made strides in multiple fields, including education. It offers transparent, secure, and decentralized storage for student records. A transparent assessment process, provided by blockchain is also vital in education. However, as the number of users and transactions grows, storage costs rise, and network performance declines. Therefore, a method is needed to increase scalability in a blockchain-based learning network, while keeping data and transactions secure. This paper presents a secure learning system using blockchain which improves the storage process, enables secure data sharing, and ensures assessment transparency through smart contracts. It utilizes a private Ethereum network and off-chain storage to enhance network performance and reduce costs. The proposed system aims to improve network scalability while maintaining security and data access control using encryption. The experimental results show that the proposed system has recorded a significant improvement in average transaction latency and has reduced file storage costs.
Chon Kit Lao, Sophie Zhou, Luyao Zhang, Fan Zhang · 5 authors
Blockchain systems such as Bitcoin and Ethereum have limitations in efficiency, resulting in an inability to immediately confirm all transactions, leading to extended periods of transactions residing in the mempool. We refer to these transactions as “long latency trans- actions” and this paper explores the issue of resource utilization in- efficiencies issues from these transactions. Utilizing the Geth client, the study quantifies the impact of these transactions on Ethereum’s resource consumption, which encompassing three crucial metrics: computational power, memory storage, and network bandwidth. Furthermore, this study also identifies three primary factors con- tributing to long latency transactions: low gas prices, long block processing times, and future-index transactions. Through empirical analysis, this study offers insights into the transaction-handling mechanisms in Ethereum. The implications of our findings aim to contribute to the enhancement of resource efficiency within the Ethereum blockchain ecosystem.
BlockVerify is a decentralized platform created to offer a safe and impenetrable way to use blockchain technology for document verification. BlockVerify guarantees the authenticity of documents by utilizing the immutability and transparency of the Ethereum blockchain. This makes it the perfect solution for individuals and organizations that need strong document verification. Users of BlockVerify can upload metadata for decentralized storage, including IPFS hashes, along with document hashes. The platform makes sure that the only people who can add and edit document records are authorized exporters who are managed and added by the contract owner. Document verification, ownership transfer, exporter management, and hash storage are important aspects. The project develops smart contracts using Solidity and Ethereum (Sepolia testnet), and it has an easy-to-use online interface using technologies like HTML, CSS and JavaScript to promote communication and MetaMask for secure wallet interactions. With future ambitions to expand to the mainnet and support new document kinds, BlockVerify intends to combat document fraud by offering a dependable way to check the legitimacy of documents.
With the rapid development and increasing maturity of emerging technologies such as 5G communication, artificial intelligence, blockchain technology, and computer supported collaborative work, the internet is entering a new era - Web3. This transformation brings both opportunities and challenges to the field of education. Addressing current issues faced by universities, such as security risks in resource storage, lack of platform creation incentives, complexity in copyright confirmation, unsatisfactory user interaction experiences, and insufficient supply of high-quality educational resources, this paper explores and proposes an innovative solution - the “CoTeach” smart education platform. This platform integrates the core concepts of Web3, and data-driven artificial intelligence technology. It aims to reshape the teaching and learning experience, as well as the collaborative development of professional knowledge. Specifically, the “CoTeach” platform ensures secure storage and immutability of educational resources through blockchain technology, reducing risks associated with resource storage. By utilizing collaborative livestreaming mechanisms, it provides economic incentives for creators, contributors, and learners, fostering greater community participation. The transparency and smart contract functionality of blockchain simplify the copyright confirmation process, safeguarding creators' rights. The platform enhances user interaction through gamification design, making the learning process more engaging and enjoyable. Finally, artificial intelligence technology optimizes resource recommendations and personalized learning paths, addressing the shortage of high-quality educational resources.
Avraam Tepelidis, Eirini E. Mitsopoulou, Athanasios T. Patenidis, Kristina Livitckaia · 6 authors
Blockchain technology advancements have made it feasible to build secure, decentralized networks with numerous use cases in various industries, including banking, education, government, and health. In higher education, there is a significant need for certification and credential verification through digital means, as fake certificates are common in the labor market. The BlockAdemiC system presented in this article falls into solutions for such issues. BlockAdemiC is a blockchain-based educational platform that makes use of cutting-edge features in blockchain technology to ensure the required degree of trust both at the individual user and institutional level. Specifically, BlockAdemiC represents a digital distributed security system for the certification and verification of educational activities, degrees, and skills in higher education and lifelong learning, producing an immutable educational passport. Information distributed using blockchain enhances trust in the exchange of information between institutions, agencies, companies, and alumni and introduces a trustworthy mechanism for content verification and authentication. For self-sovereign identity and identification management, the system utilizes distributed ledger technology via Hyperledger frameworks and offers users authority over their identities and credentials, removing the need for the involvement of central authorities to validate and verify user identities. Smart contracts are additionally supported, which provide the connection for storing student activities that take place on educational platforms on the EOSIO blockchain. The BlockAdemiC was evaluated via a technological feasibility study focusing on the system’s performance. The initial findings show that the system can efficiently process a high load of queries in parallel similar to the real-world situation and can be further considered for large-scale deployment and use.
Due to the susceptibility to nothing-at-stake and long-range attacks, the Proof-of-Stake consensus faces challenges in securely and efficiently confirming blocks. We propose a new Proof-of-Stake consensus, Voted Weightest Sub-Tree(VWeiST) consensus. It assigns weights to each block through voting, and nodes confirm blocks by calculating the probability that each block's weight can be exceeded by other competitors. We employ a multi-round voting approach, where a small number of nodes are randomly selected as the committee nodes to vote in each round. This approach results in particularly low communication overhead per block, allowing for scalability to a large number of nodes. Compared to other consensus, our mechanism requires fewer rounds of voting to confirm a block, offering advantages in throughput and transaction latency. In the experiments, VWeiST achieves latency and round reductions down to 40% and 29% of the comparison method's levels at most. Furthermore, we theoretically prove that the consensus ensures liveness and probabilistic safety.
N Nalini, V. Nageshwara Rao, K. Somasekhara Rao, P. Shobha
This research explores Decentralized Finance (DeFi) through the lens of enhanced applications, introducing the concept of Decentralized Finance Enhanced (DeFine). It examines the transformative potential of DeFi, analyzing its evolution and the innovative solutions driving its progress. The objective is to investigate how DeFine addresses scalability, interoperability, security, and user experience challenges in the DeFi ecosystem. Through case studies and analysis, this proposed work provides insights into the implications, opportunities, and risks associated with the adoption and maturation of DeFi enhancements.
Data trading is a crucial means of unlocking the value of Internet of Things (IoT) data. However, IoT data differs from traditional material goods due to its intangible and replicable nature. This difference leads to ambiguous data rights, confusing pricing, and challenges in matching. Additionally, centralized IoT data trading platforms pose risks such as privacy leakage. To address these issues, we propose a profit-driven distributed trading mechanism for IoT data. First, a blockchain-based trading architecture for IoT data, leveraging the transparent and tamper-proof features of blockchain technology, is proposed to establish trust between data owners and data requesters. Second, an IoT data registration method that encompasses both rights confirmation and pricing is designed. The data right confirmation method uses non-fungible token to record ownership and authenticate IoT data. For pricing, we develop an IoT data value assessment index system and introduce a pricing model based on a combination of the sparrow search algorithm and the back propagation neural network. Finally, an IoT data matching method is designed based on the Stackelberg game. This establishes a Stackelberg game model involving multiple data owners and requesters, employing a hierarchical optimization method to determine the optimal purchase strategy. The security of the mechanism is analyzed and the performance of both the pricing method and matching method is evaluated. Experiments demonstrate that both methods outperform traditional approaches in terms of error rates and profit maximization.
Song Yang, Keming Qiu, Fei Hu Zhang, Lu Cao · 7 authors
Edge devices (e.g., smartphones, tablelet PC, IoT devices) are becoming more prevalent in people’s daily lives. With advanced sensors and processors, these devices can create massive data. These data can be used for predictive maintenance, enhancing user experience, increasing productivity, etc. These valuable data allow data producers to sell to consumers directly to generate income. Blockchain and smart-contract technology can be used to ensure transactions to be unmodifiable and undeniable. This paper first proposes a blockchain-based data relay and transaction model for the data producer, relay and consumer in edge computing. We then present a new consensus mechanism Proof-of-Data-Trading (PoDT) by combining Proof-of-Work (PoW) mechanism with Proof-of-Stake (PoS) consensus mechanism, which enables the proposed blockchain system to reach consensus with low energy consumption for edge devices. Moreover, we develop an approximation algorithm to store encrypted copies of data items on relays with smaller costs. Extensive simulations show that our proposed blockchain system works efficiently in edge computing. It achieves up to 8.19% higher profit for the data producer with the help of relays and consumers using 84.6% less time to get the data item. In addition, the new consensus mechanism consumes 87% less time when compared with the traditional PoW consensus mechanism.
With the rapid development of Decentralized Finance (DeFi) and Real-World Assets (RWA), the importance of blockchain oracles in real-time data acquisition has become increasingly prominent. Using cryptographic techniques, threshold signature oracles can achieve consensus on data from multiple nodes and provide corresponding proofs to ensure the credibility and security of the information. However, in real-time data acquisition, threshold signature methods face challenges such as data inconsistency and low success rates in heterogeneous environments, which limit their practical application potential. To address these issues, this paper proposes an innovative dual-strategy approach to enhance the success rate of data consensus in blockchain threshold signature oracles. Firstly, we introduce a Representative Enhanced Aggregation Strategy (REP-AG) that improves the representativeness of data submitted by nodes, ensuring consistency with data from other nodes, and thereby enhancing the usability of threshold signatures. Additionally, we present a Timing Optimization Strategy (TIM-OPT) that dynamically adjusts the timing of nodes' access to data sources to maximize consensus success rates. Experimental results indicate that REP-AG improves the aggregation success rate by approximately 56.6\% compared to the optimal baseline, while the implementation of TIM-OPT leads to an average increase of approximately 32.9\% in consensus success rates across all scenarios.
Blockchain is a shared database that builds trust without third-party involvement. Its decentralized architecture ensures data is dispersed and cannot be wiped. This makes blockchain highly suitable for e-learning and online education, which have become primary means for obtaining certifications and degrees, especially with the surge in online learning due to the COVID-19 pandemic. The increase in online universities and platforms has led to issues with fraudulent coursework, poor evaluations, and degree verification. This project proposes a blockchain-based strategy for the education sector, using smart contracts to manage student data and provide success certifications.
Increasingly popular decentralized applications (dApps) with complex application logic incur significant overhead for executing smart contract transactions, which greatly limits public blockchain performance. Pre-executing transactions off the critical path can mitigate substantial I/O and computation costs during execution. However, pre-execution does not yield any state transitions, rendering the system state inconsistent with actual execution. This inconsistency can lead to deviations in pre-execution paths when processing smart contracts with multiple state-related branches, thus diminishing pre-execution effectiveness. In this paper, we develop Seer, a novel public blockchain execution engine that incorporates fine-grained branch prediction to fully exploit pre-execution effectiveness. Seer predicts state-related branches using a two-level prediction approach, reducing inconsistent execution paths more efficiently than executing all possible branches. To enable effective reuse of pre-execution results, Seer employs checkpoint-based fast-path execution, enhancing transaction execution for both successful and unsuccessful predictions. Evaluations with realistic blockchain workloads demonstrate that Seer delivers an average of 27.7× transaction-level speedup and an overall 20.6× speedup in the execution phase over vanilla Ethereum, outperforming existing blockchain execution acceleration solutions.
Ningyuan Chen, Chiew Foong Kwong, David Chieng, Pushpendu Kar
The advent of Cellular Vehicle-to-Everything (C-V2X) technology has revolutionized intelligent transportation systems (ITS), but poses challenges for secure and efficient data sharing due to its dynamic nature. Traditional centralised systems are inadequate, prompting the need for decentralised solutions like blockchain. However, applying blockchain technologies in C-V2X always faces scalability issues. This paper proposes a scalable C-V2X blockchain network integrating dynamic attribute-based sharding and zero-knowledge proofs (ZKPs). Our system ensures scalability in the C-V2X environment through sharding while utilising ZKPs to enhance cross-shard validation efficiency, reducing its complexity to O(1). Additionally, our approach reduces bandwidth consumption by 90.8% compared to Merkle tree-based solutions.
Smart contract-based applications are executed in a blockchain environment, and they cannot directly access data from external systems, which is required for the service provision of these applications. Instead, smart contracts use agents known as blockchain oracles to collect and provide data feeds to the contracts. The functionality and compatibility with smart contract applications need to be considered when selecting the best-fit oracle platform. As the number of oracle alternatives and their features increases, the decision-making process becomes increasingly complex. Selecting the wrong or sub-optimal oracle is costly and may lead to severe security risks. This article provides a decision support model for the oracle selection problem. The model supports smart contract decision-makers in selecting a secure, cost-effective, and feasible oracle platform for their applications. We interviewed oracle co-founders and smart contracts experts to refine and validate the decision model. Two real-world smart contract application case studies were used to evaluate the model. Our model prioritises and suggests more than one possible oracle platform based on the developer’s required criteria, security assessment and cost analysis. Moreover, this guided decision model serves to reveal issues that may go unnoticed if done haphazardly, reduce decision-making efforts and provide a cost-effective solution.
Blockchain technology has recently been the subject of investigation as a potential solution to security issues plaguing IoT networks. However, when dealing with a large number of IoT gadgets and the massive amounts of data produced by these networks, the inherent scalability difficulties of blockchain-based systems become obvious. Nevertheless, there are areas where the permissioned Blockchain falls short, and these include throughput and scalability. Incorporating data science methodologies, this study proposes a way to address permissioned Blockchain's scalability problem. With a variable number of transactions, the scalability study of the suggested solution is done in the hyperledger fabric architecture, which improves scalability. Because of this, we address these issues in this research by using a lightweight consensus approach. We provide a system for handling IoT data that is scalable and built on blockchain technology. It can handle data from a large number of gadgets. To guarantee improved efficiency and effectiveness in resource-constrained IoT networks, this system employs the Delegated Proof of Stake (DPoS) consensus process. DPoS mitigates the performance and effectiveness deterioration in blockchain-based IoT networks by using a certain amount of elected delegates to verify and approve transactions. It is a lightweight consensus mechanism. In this article, we used Docker, the XGBoost mapping model, and the Interplanetary File System (IPFS) to assess the network's performance in relation to latency, resource consumption, and throughput. The four components of our distributed storage study were latency, throughput, resource consumption, and the duration and speed of file uploads. We found that our framework has a low latency of less than 0.976 ms in our empirical results. One state-of-the-art consensus method, Proof of Stake (PoS), is outperformed by the suggested method. We also show that the suggested method works well for Internet of Things (IoT) uses that call for minimal latency or efficient use of resources.