Public permissionless blockchains facilitate peer-to-peer digital transactions, yet face performance challenges, specifically minimizing transaction confirmation time to decrease energy and time consumption per transaction. Performance evaluation and prediction is crucial in achieving this objective, with performance modeling as a key solution despite the complexities involved in assessing these blockchains. This survey examines prior research concerning the systems used to model blockchain performance, specifically focusing on public permissionless blockchains. Initially, it provides foundational knowledge about these blockchains and the crucial performance parameters for their assessment. Additionally, the study delves into research on the performance modeling of public permissionless blockchains, predominantly considering these systems as bulk service queues. It also examines prior studies on workload and traffic modeling, characterization, and analysis within these blockchain networks. By analyzing existing research, our survey aims to provide insights and recommendations for researchers keen on enhancing the performance of public permissionless blockchains or devising novel mechanisms in this domain.
Traditional cloud-centric approaches are facing increasing demands for instant data processing and significant challenges in meeting the latency requirements of modern applications. Edge computing emerges as a promising approach that brings computation and data storage closer to the edge of the network, enabling real-time decision-making with reduced latency and enhanced efficiency. The paper provides a comprehensive overview of edge computing, describing its fundamental principles, architectural components, and key advantages over centralized cloud infrastructures. By minimizing data transfer latency, edge computing ensures that critical data analysis and processing occur close to data sources, resulting in enhanced responsiveness and improved user experiences. The paper analyzes two case studies, including autonomous driving vehicles and finance, in order to highlight the applications of edge computing in areas where real-time decision-making is crucial. In addition to discussing the benefits of edge computing, the paper addresses the potential challenges and constraints associated with edge computing implementation. Security and privacy concerns in decentralized edge environments are explored, and several protection strategies are described. Finally, the paper outlines the future of edge computing for organizations and the technology industry. In doing so, the paper discusses the potential of edge computing in supporting emerging technologies, such as 5G networks and autonomous systems. Received: December 19, 2023Accepted: February 2, 2024
Tao Yan, Shengnan Li, Benjamin Kraner, Luyao Zhang · 5 authors
Ethereum 2.0, as the preeminent smart contract blockchain platform, guarantees the precise execution of applications without third-party intervention. At its core, this system leverages the Proof-of-Stake (PoS) consensus mechanism, which utilizes a stochastic process to select validators for block proposal and validation, consequently rewarding them for their contributions. However, the implementation of blockchain technology often diverges from its central tenet of decentralized consensus, presenting significant analytical challenges. Our study collects consensus reward data from the Ethereum Beacon chain and conducts a comprehensive analysis of reward distribution and evolution, categorizing them into attestation, proposer and sync committee rewards. To evaluate the degree of decentralization in PoS Ethereum, we apply several inequality indices, including the Shannon entropy, the Gini Index, the Nakamoto Coefficient, and the Herfindahl-Hirschman Index (HHI). Our comprehensive dataset is publicly available on Harvard Dataverse, and our analytical methodologies are accessible via GitHub, promoting open-access research. Additionally, we provide insights on utilizing our data for future investigations focused on assessing, augmenting, and refining the decentralization, security, and efficiency of blockchain systems.
In recent years, advancements in rooftop solar panel technology have sparked a revolution in the electricity markets. This has given rise to a new concept of energy exchange—the ability for consumers and producers to trade localized energy. This concept has been made possible by the emergence of blockchain technology, which has gained significant traction in the energy markets. Its unique ability to facilitate peer-to-peer (P2P) energy transactions has made it a promising solution for the trilemma of scalability, security, and decentralization. However, while blockchain technology has shown great potential, it is still in its early stages of development and has yet to reach its full potential. To fully understand the potential of blockchain technology in P2P energy trading, it is important to explore the trilemma in depth. This study proposes a blockchain-based scalability solution with a focus on P2P energy trading. This strategy is supported by empirical modeling, utilizing data gathered from a trial case study. The results of this study demonstrate that the suggested technique outperforms base-layer models in terms of scalability while still maintaining the essential elements of security and decentralization. This proposed solution not only has the potential to revolutionize the energy markets but also has broader implications. By providing a more secure and decentralized platform for P2P energy trading, it has the potential to address issues of energy distribution inequality and promote the adoption of renewable energy. With blockchain technology, individuals and communities have the opportunity to take control of their energy usage and production, reducing their reliance on traditional centralized energy systems. This not only has the potential to lower energy costs for consumers but also contributes to the overall goal of reducing carbon emissions and mitigating the effects of climate change. The combination of rooftop solar panel technology and blockchain applications has the potential to create a significant shift toward decentralized and sustainable energy systems. This will not only benefit individuals and communities but also have a positive impact on the environment and the global energy market. However, for this transition to occur, it is crucial that governments and energy companies continue to support and invest in these advancements.
Executing smart contracts is a compute and storage-intensive task, which currently dominates modern blockchain's performance. Given that computers are becoming increasingly multicore, concurrency is an attractive approach to improve programs' execution runtime. A unique challenge of blockchains is that all replicas (miners or validators) must execute all smart contracts in the same logical order to maintain the semantics of State Machine Replication (SMR). In this work, we study the maximal level of parallelism attainable when focusing on the conflict graph between transactions packaged in the same block. This exposes a performance vulnerability that block creators may exploit against existing blockchain concurrency solutions, which rely on a total ordering phase for maintaining consistency amongst all replicas. To facilitate the formal aspects of our study, we develop a novel generic framework for Active State Machine Replication (ASMR) that is strictly serializable. We introduce the concept of graph scheduling and the definition of the minimal latency scheduling problem, which we prove to be NP-hard. We show that the restricted version of this problem for homogeneous transactions is equivalent to the classic Graph Vertex Coloring Problem, yet show that the heterogeneous case is more complex. We discuss the practical implications of these results.
Abstract Scientific workflows are essential for many applications, enabling the configuration and execution of complex tasks across distributed resources. In this paper, we contribute an Ethereum blockchain-based scientific workflow execution manager, which distributes workflows to run on cluster computing providers that utilize the Slurm workload manager to execute them. We extended our blockchain-based autonomous resource broker called eBlocBroker, which is a DAO-based decentralized coordinator, by providing distributed workflow execution via blockchain. Through various tests, we demonstrate how our eBlockBroker autonomous organization, which is programmed as a smart contract, can manage scientific workflow submission, scheduling, and execution on cluster computing providers. The utilization of blockchain for distributed workflow execution is a new concept. We are motivated because our system has been developed with e-Science in mind where scientific workflows are widely utilized.
Alven C. Y. Leung, Dennis Liu, Xiapu Luo, Man Ho Au
Abstract Blockchain is a newly emerging technology in the past decade that has significantly impacted various aspects. “Scientific popularization” among IT practitioners on this technology and its use cases become a pressing need. However, constructing an effective blockchain teaching approach for this purpose is a challenging task. A training framework consisting of constructivist and pragmatic approaches is proposed, aiming to provide IT practitioners with an effective Teaching and Learning (T &L) process about blockchain on both theory and application aspects. The outcomes of this study are to 1) propose an effective teaching methodology, 2) assess the effectiveness of constructivist and pragmatic approaches and 3) extract the elements facilitating blockchain T &L. Mixed quantitative and qualitative research methods were adopted, including questionnaires and knowledge quizzes. 1267 participants were involved in the training that implemented the proposed framework. Their performance and responses indicated that the framework is effective and flexible. The findings from this empirical research can serve as a reference for educators in blockchain to implement a systemic approach that facilitates the T &L process and improves the field of blockchain and education in the future.
Ivan Malakhov, Andrea Marin, Sabina Rossi, Daniel Sadoc Menasché
Blockchains based on Proof-of-Work (PoW) have introduced a new paradigm for distributed ledgers on the Web. In these systems, transactions compete to obtain a position inside the new blocks by offering a fee to be confirmed before others. A finite amount of memory is devoted to store unconfirmed transactions, called Mempool. When new transactions arrive and the Mempool is full, silent droppings of the cheapest unconfirmed transactions occur, without any notification to the owners. This challenge becomes particularly pressing as users have the freedom to append various types of data to the blockchain, including large media files, leading to swift Mempool depletion. In this paper, we study the reliability of PoW blockchains from a user perspective. We provide a numerical model to answer the question:What is the probability of confirmation for a transaction offering a fee$f$when the system is in a certain state?Our model allows blockchain-based applications to analyse the tradeoff between running costs and reliability, i.e., fees offered for the transactions and probability that the transactions will be eventually confirmed. The proposed method is proactive and does not require historical data on dropped transactions that, in fact, are not logged anywhere in the blockchain. This paper presents significant contributions, summarized as follows: (i) the introduction of a stochastic model and its efficient solution for analyzing dropping probability in blockchain systems; (ii) validation of the model through real traces extracted from the Bitcoin blockchain.
Fog computing, a paradigm that extends cloud computing closer to the edge of the network, has emerged as a transformative solution to address the growing demands of latency-sensitive applications and the massive influx of data from the Internet of Things (IoT). Unlike traditional cloud computing, which centralizes data processing and storage in distant data centers, fog computing leverages a distributed architecture, bringing computation, storage, and networking resources closer to the end-users and devices. This abstract explores the key concepts, principles, and advantages of fog computing. By distributing computing resources across a continuum from the cloud to the edge, fog computing minimizes latency, enhances efficiency, and optimizes network bandwidth. The seamless integration of edge devices into the computing infrastructure facilitates real-time processing of data, enabling timely decision-making and improved user experiences in applications ranging from autonomous vehicles to smart cities. Furthermore, the abstract delves into the architectural components of fog computing, including fog nodes, gateways, and the interaction with cloud resources. The dynamic nature of fog environments allows for scalable and flexible deployments, catering to the diverse requirements of modern applications. Security and privacy concerns are also addressed, emphasizing the need for robust mechanisms to protect data integrity and user confidentiality in decentralized computing environments. As the digital landscape continues to evolve, fog computing emerges as a pivotal enabler of edge intelligence, empowering organizations to harness the benefits of real-time data processing and analysis at the edge of the network. The adoption of fog computing signifies a paradigm shift in the way we approach data management and processing, opening new avenues for innovation and efficiency in the era of the Internet of Things. Keywords: IOT, Fog Computing, Autonomous Vehicles.
Parwinder Singh, Michail J. Beliatis, Mirko Presser
Dataspace and emerging technologies play a key role in developing value chain systems using cross-domain data, services and systems integration. Therefore, this study has conducted a comprehensive literature review for six years (2017-2022) on the convergence of Internet of Things (IoT), Artificial Intelligence (AI) and Distributed Ledger (Blockchain) technologies for supporting Dataspace integration efforts at the Edge. As an outcome, this study has identified relevant challenges that include heterogeneity, integration and interoperability, distributed security, trust, scalability, and resource management. It has also been found that very limited research covers the architectural aspects of distributed edge in the context of the convergence of technologies for Dataspace integration purposes. Therefore, this study has proposed an architectural framework - Distributed Edge Network Operations-oriented Semantic (DENOS) model that extends the traditional Cloud-Edge-Device architecture with three new layers - Semantic, Convergence, and Dataspace integration. In addition, the model leverages the power of semantic modelling (i.e., Processing, Service, and Data) context, which enables the model to have a dynamic implementation context to suit the diverse needs of target use cases. To showcase the validation of the model, a use case related to the digital traceable operation of the wind energy domain has been presented. The objective of the DENOS model is to enable Dataspace integration to build edge-enabled value chain networks. Thus, it contributes to secure and semantic integration using the convergence of resources and technologies, cross-domain collaboration, reusability and data-driven decision-making of resources.
Md Arif Hassan, Cong T. Nguyen, Chi-Hieu Nguyen, Dinh Thai Hoang · 6 authors
Web 3.0 is the third generation of the World Wide Web (WWW), concentrating on the critical concepts of decentralization, availability, and increasing client usability. Although Web 3.0 is undoubtedly an essential component of the future Internet, it currently faces critical challenges, including decentralized data collection and management. To overcome these challenges, blockchain has emerged as one of the core technologies for the future development of Web 3.0. In this paper, we propose a novel blockchain-based information management framework, namely Smart Blockchain-based Web (SBW), to manage information in Web 3.0 effectively, enhance the security and privacy of users’ data, bring additional profits, and incentivize users to contribute information to the websites. Particularly, SBW utilizes blockchain technology and smart contracts to manage the decentralized data collection process for Web 3.0 effectively. Moreover, in this framework, we develop an effective consensus mechanism based on Proof-of-Stake (PoS) to reward the user’s information contribution and conduct game theoretical analysis to analyze the user’s behavior in the considered system. Additionally, we conduct simulations to assess the performance of SBW and investigate the impact of critical parameters on information contribution. The findings confirm our theoretical analysis and demonstrate that our proposed consensus mechanism can incentivize the nodes and users to contribute more information to our systems.
Muhammad Ahmad Ashfaq, Nimra Haq, Usman Arshad, Muhammad Shoaib Farooq · 5 authors
ATMs generate vast amounts of data daily, which needs to be analyzed and stored. Dealing with this data, also termed big data, is a complex task, and here comes the role of ETL pipelines. ETL pipelines need extensive resources for operations, and their performance optimization is necessary as data must be dealt with in near or even real-time. If the pipeline deals with financial data such as ATM transactions, steps should be taken to ensure the data's security, privacy, confidentiality, and integrity. This can be achieved using Blockchain technology. It is a distributed ledger technology having an immutable nature. It has significant advantages in terms of providing security, but it has disadvantages as well, such as low throughput and transactional latency. If blockchain is used in an ETL pipeline, it will affect the overall performance. So, to prevent the decline in performance, steps should be taken to optimize it. In this paper, we are using parallelization and partitioning as techniques to optimize performance. The primary goal here is to achieve maximum security while maintaining performance.
Patikiri Arachchige Don Shehan Nilmantha Wijesekara
Load Balancing (LB) in networking attempts to minimize the under-utilization and over-utilization of network resources by distributing the network flows evenly in the communication network. Blockchain includes a string of joined blocks that are built into the preservation of the non-tampering nature and safeguarding the verifiability. According to our felt experience, we are the initiators to review on blockchain-driven LB, where we organize the blockchain-driven LB concept under 7 categories and interpret thoroughly their performance in relation to LB techniques, BC-driven variables, LB approach, network variables, and similar things. We accumulated an early sample of 76 paper citations by handpicking articles for eligibility requirements scrutinized from web repositories, deploying a thorough and continuous method. Relying on this assessment, blockchain has been deployed in network LB for protecting data fidelity, trustworthiness, confidentiality of data transfers, deploying blockchain consensus for LB, deploying smart contracts for LB, deploying with secure resource trading, access control, and as a coordinator in the system of LB. Moreover, LB involves balancing loads in the blockchain transactions themselves. Thorough interpretation depicts that from blockchaindriven LB schemes, 37.5% deploy blockchain transaction LB, 90% deploy conventional blockchain architecture, 30% deploy generic consensus, 97.5% deploy decentralized LB, 97.5% deploy dynamic LB, 52.5% deploy deterministic LB, and the majority target generic networks. Finally, we go over the potential and predicaments of the notion of blockchain-driven LB and then provision ideas to defeat them.
The thriving Internet of Things, a paradigm shift from the traditional Internet has brought about great societal improvements such as smart homes, smart cities, smart health, intelligent systems and many more. With these diverse societal improvements come increasing complexities in the areas of system efficiency, privacy, and security. In recent years ample academic and industrial research have delved into resource optimization to the detriment of security, as security features are left to be bolted on at the end of design and developmental processes. This approach leaves the system susceptible to threats and attacks. Consequently, this paper seeks to incorporate security features from the onset, weaving the security feature into the system's design and developmental phase. The proposed model structured in a three-tiered design comprises of concepts of Blockchain, edge computing, clustering techniques and a hybrid algorithm consisting of the static round-robin and the dynamic resource-based algorithms. The composition of the structural layout which considers aspects of the blockchain as a security tight measure for resource optimization in Internet of Things' environment, also incorporates features of edge computing, clustering techniques and the hybrid algorithm as components for resource optimization of the Internet of Things. In addition to the prospective security feature provided by the Hyperledger fabric BC in the proposed model, simulation results illustrate the Hyperledger fabric BC's dexterity in making IoT systems even more efficient, further showing its efficacy over the PSOR2B and the BC-EDSSP.
Support tools that monitor software application processes are required to identify, measure, and assess their performance and resolve any anomalies that impede their full functionality. Similarly, applications that use blockchain technology require analysis and monitoring tools for the resources and functionality provided by their smart contracts. This paper presents a computational tool that monitors hardware resources and evaluates transaction processing requests in blockchain networks. The solution presented here is called MonitorChain, and it has software components that allow the connection with different blockchain networks, the configuration of the workload, the monitoring of consumed hardware resources, and the evaluation of requests processed over blockchain networks. The effectiveness and adaptability of MonitorChain were validated through extensive evaluations across various blockchain environments, including public networks like Ethereum, Avalanche, and Fantom, as well as a private network using Hyperledger Fabric, with a consistent data load of 10,000 transactions. Additionally, through interviews with experienced software developers, we gathered feedback that led to further refinements and identified opportunities for future enhancements. The results demonstrated MonitorChain’s capability to provide critical insights into blockchain applications’ performance, scalability, and efficiency. MonitorChain advances the field compared to existing solutions by offering enhanced support for diverse networks, customizable workloads, and real-time data visualization, contributing significantly to the blockchain monitoring landscape.
This work proposes an end-to-end architecture for secure data federation and privacy-preserving analytics across multi-tenant cloud environments using homomorphic encryption (HE). We address the core challenge of enabling cross-tenant joins, aggregations, and model scoring without exposing plaintext or weakening tenant isolation. The framework integrates schema-level federation with encrypted data lakes, columnar ciphertext packing for vectorized operations, and an adaptive HE planner that selects between CKKS for approximate analytics and BFV/BGV for exact computations. To bound latency while maintaining correctness, we apply batching, ciphertext relinearization, and rotation scheduling, and offload heavy primitives to accelerator-ready microservices. Policy-aware orchestration enforces per-tenant keys via cloud KMS and supports fine-grained access control and revocation. For sensitive workflows, we compose HE with complementary protections secure enclaves for control-plane logic, differential privacy on result releases, and zero-knowledge proofs to attest query policy compliance achieving defense-in-depth without collapsing the HE trust model. The system exposes SQL-like and DataFrame APIs, a query optimizer that estimates noise budgets and bootstrapping costs, and lineage-rich audit trails for regulatory reporting. We outline deployment patterns on containerized clusters, discuss cost/performance trade-offs under realistic workloads, and provide guidance on tenancy hardening (noisy neighbor resistance, side-channel hygiene). The result is a practical pathway for organizations to collaborate on analytics and machine learning across clouds and jurisdictions while preserving confidentiality, minimizing data movement, and meeting compliance obligations
The need for patient-centered electronic records that can store and retrieve the myriad details of a patient's medical history as documented during treatment has increased dramatically.These records are vital for future care, billing, or treatment.The distributed ledger technology known as Blockchain enables us to store this data and start and enable use at lightning speed while keeping the system transparent and secure.Using a distributed system with ledger capability allows for the safe and interoperable storage of records.With the elimination of mediators in financial and data transactions and in verifying data authenticity and ownership records, blockchain technology promises to alter the current state of digital asset transactions radically.Its extensive files and easy access to patients' medical histories are two of the most critical issues in healthcare, and its immutability, decentralization, and openness make it an ideal solution.Interoperability, the ability of various health organizations and software product makers to connect and exchange data securely and smoothly, is crucial to healthcare systems' practical and successful operation.Lack of interoperability is the root cause of many difficulties in contemporary healthcare, including data silos and disparate workflow tools.To solve this problem, a system that allows safe, recognized medical records to be kept in separate databases should be implemented.Using fog computing, which can decentralize data processing and handle massive amounts of data, we reviewed the literature and performed a system overview of blockchain technology in this study.Our ongoing experimental study highlights areas where current systems are lacking and suggests potential avenues for further research.
Junaid Nasir Qureshi, Muhammad Shoaib Farooq, Adel Khelifi, Zabihullah Atal
Distributed Scrum of Scrums Agile Software Development (DSsASD) plays a crucial role in modern software development, enabling collaboration across vast distances in software development. However, existing tools and frameworks have struggled to effectively address communication, teamwork, and collaboration challenges within DSsASD teams. These challenges include transparency, trust, traceability, auditability, and security concerns, these issues are related to project delays, client dissatisfaction, contract cancellations, miscommunication collaboration, and payment disputes between stakeholders. To tackle these persistent concerns and issues, this article introduces ChainAgilePlus, a novel framework that integrates blockchain technology in the distributed scrum of scrum agile software development. ChainAgilePlus implements smart contracts by utilizing a private Ethereum blockchain to govern acceptance acknowledgment, deployment testing, secure payments, verification of developer payments, and automated payment distribution to team wallets. Smart contracts also enforce penalties for delayed payments and overdue tasks, promoting accountability and adherence to deadlines. Additionally, ChainAgilePlus mitigates blockchain scalability challenges by integrating the Interplanetary File System (IPFS) for off-chain storage. Empirical results from experimental processes demonstrate the effectiveness of ChainAgilePlus in enhancing communication, transparency, coordination, traceability, auditability, security, and trust among clients and developers in DSsASD projects.
Introduction/purpose: This work provides a comprehensive overview of blockchain technology, elucidating its foundational principles and how it ensures transparency, immutability, and decentralization. The integration of Solidity with blockchain is explored through theoretical approach. Methods: This work meticulously dissects blockchain principles, elucidating transparency, immutability, and decentralization, while exploring Solidity integration in a theoretical framework, ensuring a comprehensive understanding of their intricate relationship and contributing to a broader comprehension of modern distributed ledger technology. Results: The resulting product of this paper will be getting useful knowledge about the technology that practically shapes the world. Conclusion: In conclusion, the adoption of Solidity as a programming language in blockchain technology has proven to be pivotal, enhancing smart contract functionality and overall system security. Its specialized features make it an indispensable tool for developers navigating the complexities of decentralized applications.
Blockchain is an emerging technology with Big data, Artificial Intelligence, and Machine Learning. It disrupted industries such as health, education, manufacturing, and banking. However, the increasing popularity of Blockchain ex- poses the scalability issues of major public blockchain platforms (e.g., Bitcoin and Ethereum) and dramatically affects its development. The scalability problem manifests in terms of Low throughput, high transaction latency, and massive energy consumption. Several reviews and studies cover these factors and their potential solutions, yet these studies need to highlight more information through actual application to natural systems or projects. This study investigates all relevant papers on current research solutions for public blockchain scalability issues. The scope of this paper is to explore the implementation of different state-of-the-art scalability solutions to natural systems and projects while simultaneously highlighting the results. This study discusses the methods and techniques used and the challenges encountered that have yet to future researchers must explore.
Oleksandr Ulichev, Oleksandr Dorenskyi, Victor Kulahin
The rapid advancement of technology and increasing market competition compel businesses to adapt swiftly by implementing new features and services to meet user demands. Traditional monolithic software architectures often hinder this agility due to challenges in scalability and maintenance. This article aims to analyze microservice architecture to solve these challenges, exploring its historical development, current trends, practical implementation aspects, and comparison with alternative architectural styles such as modulith architecture. The study examines the limitations of monolithic architectures in handling growing complexity and scaling requirements. It explores the emergence of microservice architecture, highlighting core characteristics like independent services, decentralized data management, and autonomous deployment. The evolution influenced by agile methodologies and DevOps practices is discussed. A comparative analysis with other architectural styles—including monolithic, service-oriented, modular monolithic, and serverless architectures—identifies contexts where microservices are most beneficial. The research reviews essential tools and technologies for implementing microservices, such as Docker for containerization, Kubernetes for orchestration, and service meshes like Istio and Linkerd. Practical cases from industry leaders like Netflix and Amazon illustrate successful adoption and the challenges faced during implementation. Findings indicate that while microservice architecture offers significant scalability, flexibility, and rapid deployment advantages, it also introduces complexities related to distributed system management and security. The study emphasizes the importance of adopting best practices and standards, such as those promoted by the Cloud Native Computing Foundation and utilizing modern tools to mitigate these challenges. For organizations where full microservices adoption may be impractical, modulith architecture is a viable alternative that combines modularity with deployment simplicity. The article concludes that the choice of architecture should be carefully aligned with the project's specific needs, resources, and long-term strategic goals.