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.
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.
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.
This comprehensive article explores the transformative integration of edge computing and hybrid cloud storage, a technological convergence that is reshaping data processing architectures in the era of exponential data growth. The research delves into the fundamental principles of edge computing and hybrid cloud storage, examining their synergistic relationship in addressing the limitations of traditional centralized cloud computing. By bringing computational resources closer to data sources, this integrated approach significantly reduces latency, enhances processing efficiency by up to 50%, and improves overall system reliability. The article presents detailed case studies in autonomous driving and smart city infrastructure, showcasing real-world applications and benefits. It critically analyzes the challenges inherent in this integration, including security concerns in decentralized architectures, data consistency issues, and cost implications. Furthermore, the article explores future directions, discussing emerging technologies such as AI-powered edge devices, evolving hybrid cloud solutions, and the potential for further optimization. This research provides valuable insights for organizations and researchers navigating the complex landscape of distributed computing, offering a roadmap for leveraging edge computing and hybrid cloud storage to achieve unprecedented levels of performance, scalability, and flexibility in data management and processing.
A. Jabbari, Gowri Ramachandran, Sidra Malik, Raja Jurdak
In the current digital landscape, supply chains have transformed into complex networks driven by the Internet of Things (IoT), necessitating enhanced data sharing and processing capabilities to ensure traceability and transparency. Leveraging Blockchain technology in IoT applications advances reliability and transparency in near-real-time insight extraction processes. However, it raises significant concerns regarding data privacy. Existing privacy-preserving approaches often rely on Smart Contracts for automation and Zero Knowledge Proofs (ZKP) for privacy. However, apart from being inflexible in adopting system changes while effectively protecting data confidentiality, these approaches introduce significant computational expenses and overheads that make them impractical for dynamic supply chain environments. To address these challenges, we propose ZK-DPPS, a framework that ensures zero-knowledge communications without the need for traditional ZKPs. In ZK-DPPS, privacy is preserved through a combination of Fully Homomorphic Encryption (FHE) for computations and Secure Multi-Party Computations (SMPC) for key reconstruction. To ensure that the raw data remains private throughout the entire process, we use FHE to execute computations directly on encrypted data. The "zero-knowledge" aspect of ZK-DPPS refers to the system's ability to process and share data insights without exposing sensitive information, thus offering a practical and efficient alternative to ZKP-based methods. We demonstrate the efficacy of ZK-DPPS through a simulated supply chain scenario, showcasing its ability to tackle the dual challenges of privacy preservation and computational trust in decentralised environments.
Tarek Zaarour, Ahmed Khalid, Preeja Pradeep, Ahmed H. Zahran
Knowledge graphs have proven vital for efficient data management, enhanced search capabilities, and improved decision-making in various information technology domains. However, constructing reliable knowledge graphs in decentralized ecosystems, with distributed autonomous actors, poses significant challenges related to asynchronous transmission, out-of-order knowledge-sharing, device heterogeneity, and trust issues. These challenges are also present in resource orchestration within multi-cloud edge ecosystems where multiple stakeholders must collaborate and share information to enable next-gen smart applications. In this paper, we propose a novel system design that utilizes Distributed Ledger Technology to build knowledge graphs. This approach ensures consistent and trustworthy knowledge sharing among orchestrators in a cloud-edge continuum. Our solution accommodates diverse requirements of both cloud and edge servers, allowing clients to construct complete historic graphs or build filtered sub-graphs. We deploy our solution in a multi-cloud edge environment and construct knowledge graphs representing the system state, including clusters, servers, microservices, and various resources. We validate the feasibility and performance of our solution through a real-world deployment and experiments in a smart shopping use case. Results demonstrate that the proposed solution achieves the claimed benefits with minimal or acceptable delays in comparison to traditional event streaming services.
The IoT devices are growing rapidly, which has led to an exponential rise in the amount of data those devices are producing. There is a pressing need for effective and secure data transfer techniques from IoT devices to the cloud as the amount and complexity of IoT data keep growing. This paper introduces a revolutionary idea that combines fog computing, and blockchain technology and also uses a hybrid consensus mechanism to ensure secured data transmission between IoT and Cloud. Fog computing, a branch of the cloud provides local processing, storage, and communication capabilities. By leveraging fog computing, data transmission latency is reduced, and network congestion is minimized, resulting in improved performance and responsiveness. Blockchain technology is incorporated into the system to guarantee the security of IoT data while it is being transmitted. Blockchain, with its decentralized and immutable nature, provides a transparent and tamper-proof ledger for recording data transactions. Each data transaction from an IoT device is encrypted, timestamped, and appended to the blockchain, creating an auditable and trustworthy record of data transmission. Additionally, a hybrid consensus mechanism using Delegated Proof of Stake and Practical Byzantine Fault Tolerance is employed to validate the transaction. This concept addresses the challenges of data security, latency, and integrity in IoT applications, enabling the development of scalable and trustworthy IoT systems across various industries. The efficiency of the proposed system is validated by evaluating performance metrics such as latency, accuracy, precision, recall, F-score, and verification time, and comparing the results with those of existing approaches. The implemented systems, tailored for the healthcare domain, exhibit security measures and an impressive 18% reduction in latency, while enhancing the accuracy by 15% when compared to the conventional approach, as per the experimental results.
Sana Naz, Mohsin Javaid Siddiqui, Scott Uk-Jin Lee
To be a stakeholder/validator/token holder is not so difficult in the Proof of Stake (POS)-based blockchain networks; that is why the number of validators is large in these networks. These validators play an essential part in the block creation process in the PoS-based blockchain network. Due to the large validators, the block creation time and communication message broadcasting overhead get increased in the network. Many consensus algorithms use different techniques to reduce the number of validators, such as Delegated Proof of Stake (DPoS) consensus algorithms, which select the set of delegators via stake transactions for the block creation process. In this paper, we propose S&SEM, a secure and speed-up election process to select the ‘z’ number of validators/delegators. The presented election process is based on a traditional voting style with multiple numbers of rounds. The presented election mechanism reduces the possibility of malicious activity in the voting process by introducing a special vote message and a round that checks duplicate votes. We did horizontal scaling in the network to speed up the election process. We designed an improved incentive mechanism for the fairness of the election process. The designed reward and penalty procedure controls the nodes’ behaviors in the network. We simulate the S&SEM, and the result shows that the presented election process is faster and more secure to select delegators than the existing process used by DPOS.
Zero-knowledge layer 2 protocols emerge as a compelling approach to overcoming blockchain scalability issues by processing transactions through the transaction finalization process. During this process, transactions are efficiently processed off the main chain. Besides, both the transaction data and the zero-knowledge proofs of transaction executions are reserved on the main chain, ensuring the availability of transaction data as well as the correctness and verifiability of transaction executions. Hence, any bugs that cause the transaction finalization failure are crucial, as they impair the usability of these protocols and the scalability of blockchains. In this work, we conduct the first systematic study on finalization failure bugs in zero-knowledge layer 2 protocols, and define two kinds of such bugs. Besides, we design fAmulet, the first tool to detect finalization failure bugs in Polygon zkRollup, a prominent zero-knowledge layer 2 protocol, by leveraging fuzzing testing. To trigger finalization failure bugs effectively, we introduce a finalization behavior model to guide our transaction fuzzer to generate and mutate transactions for inducing diverse behaviors across each component (e.g., Sequencer) in the finalization process. Moreover, we define bug oracles according to the distinct bug definitions to accurately detect bugs. Through our evaluation, fAmulet can uncover twelve zero-day finalization failure bugs in Polygon zkRollup, and cover at least 20.8% more branches than baselines. Furthermore, through our preliminary study, fAmulet uncovers a zero-day finalization failure bug in Scroll zkRollup, highlighting the generality of fAmulet to be applied to other zero-knowledge layer 2 protocols. At the time of writing, all our uncovered bugs have been confirmed and fixed by Polygon zkRollup and Scroll zkRollup teams.
Andrey L. Bulgakov, Anna V. Aleshina, Sergey D. Smirnov, Alexey D. Demidov · 6 authors
This article addresses the issues of scalability and security in blockchain networks, with a focus on sharding algorithms and decentralized data storage. Key challenges include the low throughput and high transaction latency in public networks such as Bitcoin and Ethereum. Sharding is examined as a method to enhance performance through data distribution, but it raises concerns regarding node management and reliability. Sharding schemes, such as Elastico, OmniLedger, Pyramid, RepChain, and SSchain, are analyzed, each presenting its own advantages and drawbacks. Alternative architectures like Directed Acyclic Graphs (DAGs) demonstrate potential for improved scalability but require further refinement to ensure decentralization and security. Protocols such as Brokerchain, Meepo, AHL, Benzene, and CycLedger offer unique approaches to addressing performance and transaction consistency issues. This article emphasizes the need for a comprehensive approach, including dynamic sharding, multi-level consensus, and inter-shard coordination. Additionally, a conceptual model is proposed that incorporates the sharding of transactions, states, and networks, which enables greater scalability and efficiency.
Securing interoperable and sovereign data exchange in the Industrial Internet of Things (IIoT) for machine data exploitation by third parties presents a significant challenge. This work addresses this by integrating IOTA Distributed Ledger Technology (DLT) with the International Data Spaces (IDS) Reference Architecture Model (RAM), creating a decentralized data space optimized for IIoT ecosystems. This research demonstrates the practical implementation of core IDS architectural concepts within the IOTA framework, overcoming theoretical DLT limitations and showcasing IOTA’s capability to enhance data sovereignty and interoperability in the IIoT, moving beyond traditional blockchains, which are constrained by scalability and efficiency issues. It sets the stage for future evaluations and broader applicability studies, paving the way for advancements in secure, sovereign, interoperable, and efficient data management.
George Danezis, Lefteris Kokoris-Kogias, Alberto Sonnino, Mingwei Tian
Obelia improves upon structured DAG-based consensus protocols used in proof-of-stake systems, allowing them to effectively scale to accommodate hundreds of validators. Obelia implements a two-tier validator system. A core group of high-stake validators that propose blocks as in current protocols and a larger group of lower-stake auxiliary validators that occasionally author blocks. Obelia incentivizes auxiliary validators to assist recovering core validators and integrates seamlessly with existing protocols. We show that Obelia does not introduce visible overhead compared to the original protocol, even when scaling to hundreds of validators, or when a large number of auxiliary validators are unreliable.
Sushanth Sreenivasamurthy Manakhari, Ajinkya P. Jadhav, Twinkle Paraye, Anurag Gate
In the evolving landscape of digital data management, blockchain technology emerges as a transformative force, particularly through its implementation within Ethereum. This paper delves into the role of Ethereum in enhancing data accessibility across distributed file systems. By leveraging the power of smart contracts, Ethereum introduces a level of automation and reliability previously unattainable in traditional systems. The integration of Ethereum with decentralized storage solutions like the Inter Planetary File System (IPFS) facilitates not only more transparent and efficient access to data but also augments security and trustworthiness. We explore the technical mechanisms by which Ethereum smart contracts automate data operations and how these interactions enhance system performance and user experience. Furthermore, the paper discusses the potential challenges and solutions associated with integrating blockchain technologies into existing data systems, thereby providing insights into their future implications for the global data economy. The findings indicate that Ethereum substantially increases accessibility, reduces operational bottlenecks, and could pave the way for new data governance models that are secure, efficient, and scalable.
Ethereum has adopted a rollup-centric roadmap to scale its network while preserving both security and decentralization. Rollups are layer 2 scaling solutions that process transactions off-chain while posting summarized data on-chain to maintain security and reduce costs. Posting data on-chain remains expensive, which led to the introduction of blobs via EIP-4844 that offer a cost-effective solution for data availability (DA). Although blobs significantly reduce DA costs compared to traditional calldata, many cost-sensitive small rollups struggle to fully utilize the fixed blob capacity. Blob sharing, which allows multiple rollups to collaboratively utilize a single blob, has been proposed as a solution to these challenges. In this paper, we empirically analyze nearly six months of data to assess the effectiveness of blob sharing. Our simulation results demonstrate that blob sharing can lower overall costs by approximately $\mathbf{8 0 \%}$ to 99%. These findings imply that the benefits of blob sharing are even greater than initially expected, providing strong incentives for both small and big rollups to actively collaborate in its adoption.
Blockchain technology has recently received a great deal of attention from industry and academia due to its apparent benefits. From the initial foundation based on cryptocurrency to the development of smart contracts, Blockchain technology continues to promise significant business benefits for various industry sectors. Notwithstanding its known benefits, and despite having some protective measures and security features, this technology still faces significant security challenges within its different abstract layers. This work focuses on the critical cybersecurity threats and vulnerabilities inherent to the different layers of the Blockchain architecture, with a view to mitigate against the associated risks. From the perspective of architectural layering, each layer of the Blockchain has its own corresponding security issues. In this work, a seven-layer architecture is used, whereby the various components of each layer are set out, highlighting the related security risks and corresponding countermeasures. A taxonomy is then developed, that establishes the inter-relationships between the vulnerabilities and attacks in a smart contract. A specific emphasis is placed on the issues caused by centralisation within smart contracts, whereby a “one-owner” controls access, thus threatening the very decentralised nature that Blockchain is based upon. Smart contracts with centralised ownership pose major security issues and act as a single point of failure, allowing single individuals, or teams, to have complete control over the Blockchain network. To mitigate against the risks associated with centralised control, decentralised autonomous organisations (DAOs) promote a decentralised decision-making process whereby the power of decision-making is distributed and therefore preventing smart contract ownership monopoly. The main contribution of this thesis is the development of a novel automated decentralised application, “Genuine DAO”, that promises to reduce security risks and improve the performance of Blockchain networks. “Genuine DAO” achieves the reduction in security risks by enforcing automated rules that are encoded in smart contracts thus reinforcing the community-based governance and minimising the threats inherent to centralisation, which can be caused by smart contracts’ owners/developers. Additionally, “Genuine DAO” strengthens the security of the network by guarding against the threats caused by Frontrunning attacks. Three further contributions emanate from this work. The first one is an improvement of the overall performance of the Blockchain network, through gas optimisation, cost reduction, and network throughput. This is achieved by using a Polygon layer 2 scaling solution built on the Ethereum network. The second one is the development of a general taxonomy that compiles the different vulnerabilities, the types of attacks, and the related countermeasures within each of the seven layers of the Blockchain. The third one stems from a deep dive into one layer of the Blockchain namely, the Contract Layer. A model application is developed depicting, in detail, the security risks within the Contract Layer, while enlisting the best practices and tools to adopt in order to mitigate against these risks. The understanding gained from delving into the details of security risks within the Contract Layer reinforced the need for developing countermeasures to alleviate the security risks and vulnerabilities inherent to one-owner control in smart contracts, which ultimately led to the main contribution of this work: Genuine DAO.
This paper surveys innovative protocols that enhance the programming functionality of the Bitcoin blockchain, a key part of the "Bitcoin Ecosystem." Bitcoin utilizes the Unspent Transaction Output (UTXO) model and a stack-based script language for efficient peer-to-peer payments, but it faces limitations in programming capability and throughput. The 2021 Taproot upgrade introduced the Schnorr signature algorithm and P2TR transaction type, significantly improving Bitcoin's privacy and programming capabilities. This upgrade has led to the development of protocols like Ordinals, Atomicals, and BitVM, which enhance Bitcoin's programming functionality and enrich its ecosystem. We explore the technical aspects of the Taproot upgrade and examine Bitcoin Layer 1 protocols that leverage Taproot's features to program non-fungible tokens (NFTs) into transactions, including Ordinals and Atomicals, along with the fungible token standards BRC-20 and ARC-20. Additionally, we categorize certain Bitcoin ecosystem protocols as Layer 2 solutions similar to Ethereum's, analyzing their impact on Bitcoin's performance. By analyzing data from the Bitcoin blockchain, we gather metrics on block capacity, miner fees, and the growth of Taproot transactions. Our findings confirm the positive effects of these protocols on Bitcoin's mainnet, bridging gaps in the literature regarding Bitcoin's programming capabilities and ecosystem protocols and providing valuable insights for practitioners and researchers.
The coming of Distributed Ledger Technologies (DLTs) and blockchain, in the outlook of new technologiesduring the last decade, entailed a disruption in several spheres, such as the economy field and the identificationof entities and individuals, due to the great possibilities provided to them. Although their first application were cryptocurrencies, DLTs have been assimilated in other settings, suchas their introduction in enterprise-grade systems. The technology itself has been evolving, facing some of itslimitations and accommodating the extension of its potential use cases. SIGMA is conceived to broaden knowledge in two of the most novel aspects of DLTs: Layer-2 networksand decentralized self-sovereign identity. Its goal is to increase expertise in these areas to facilitate theirintegration and exploitation by our surrounding companies.
Distributed Ledger Technologies (DLTs) promise decentralization, transparency, and security, yet the reality often falls short due to fundamental governance flaws. Poorly designed governance frameworks leave these systems vulnerable to coercion, vote-buying, centralization of power, and malicious protocol exploits-threats that undermine the very principles of fairness and equity these technologies seek to uphold. This article surveys the state of DLT governance, identifies critical vulnerabilities, and highlights the absence of universally accepted best practices for good governance. By bridging insights from cryptography, social choice theory, and e-voting systems, we not only present a comprehensive taxonomy of governance properties essential for safeguarding DLTs but also point to technical solutions that can deliver these properties in practice. This work underscores the urgent need for robust, transparent, and enforceable governance mechanisms. Ensuring good governance is not merely a technical necessity but a societal imperative to protect the public interest, maintain trust, and realize the transformative potential of DLTs for social good.
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.
Blockchain is increasingly offered as blockchain-as-a-service (BaaS) by cloud service providers. However, configuring BaaS appropriately for optimal performance and reliability resorts to try-and-error. A key challenge is that BaaS is often perceived as a ``black-box,'' leading to uncertainties in performance and resource provisioning. Previous studies attempted to address this challenge; however, the impacts of both vertical and horizontal scaling remain elusive. To this end, we present machine learning-based models to predict network reliability and throughput based on scaling configurations. In our evaluation, the models exhibit prediction errors of ~1.9%, which is highly accurate and can be applied in the real-world.
Sharding is a critical technology for enhancing blockchain scalability. However, existing sharding blockchain protocols suffer from a high cross-shard ratio, high transaction latency, limited throughput enhancement, and high account migration. To address these problems, this paper proposes a sharding blockchain protocol for enhanced scalability and performance optimization through account transaction reconfiguration . Firstly, we construct a blockchain transaction account graph network structure to analyze transaction account correlations. Secondly, a modularity-based account transaction reconfiguration algorithm and a detailed account reconfiguration process is designed to minimize cross-shard transactions. Finally, we introduce a transaction processing mechanism for account transaction reconfiguration in parallel with block consensus uploading, which reduces the reconfiguration time overhead and system latency. Experimental results demonstrate substantial performance improvements compared to existing shard protocols: up to a 34.7% reduction in cross-shard transaction ratio, at least an 83.2% decrease in transaction latency, at least a 52.7% increase in throughput and a 7.8% decrease in account migration number. The proposed protocol significantly enhances the overall performance and scalability of blockchain, providing robust support for blockchain applications in various fields such as financial services , supply chain management , and industrial Internet of Things . It also enables better support for high-concurrency scenarios and large-scale network environments.
Maria do Rosário de Fátima Martins Ferreira, Bernardo Ferreira de Moura Ribeiro, Alcemir Rodrigues Santos, Ricardo de Andrade Lira Rabêlo
Blockchain technology is no longer just about cryptocurrencies.Companies are increasingly exploring the use cases available to increase the added value of their products and services, as well as improving the security and strengthening the trust of their systems.However, developing and maintaining applications based on this technology is still a major challenge, especially when it comes to integrating them with various web applications, what are now known as Web3 applications.Hyperledger FireFly has emerged as a solution with the potential to ease new developers onto the path of developing such applications.Considering the scarcity of teaching material, as well as learning opportunities for beginners in this technology, this chapter proposes an introductory experience for this target audience to get started in the development of Web3 applications.