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.
Blockchain technology and non-fungible tokens (NFTs) are transforming industries like finance, art, and gaming. This chapter explores their intersection and profound implications for sustainable investments. Blockchain's transparency and immutability enhance trust in sustainability projects, while NFTs tokenizing real-world assets democratize access and promote eco-friendly initiatives. Real-world cases demonstrate the practical impact of blockchain-driven NFTs in sectors like renewable energy, sustainable agriculture, and carbon credits. Challenges include regulatory frameworks and environmental concerns, but the future promises a more robust ecosystem, increased accessibility, and greater transparency in sustainable finance.
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.
Peer-to-Peer (P2P) Energy Trading Prototype Implementation is presented in this paper. This study aims to design a prototype and implement it with a P2P energy trading system, private Ethereum blockchain, and WebSocket. A Raspberry Pi 3 Model B (Pi3B) hosts the WebSocket server for creating the duplex communication including the current sensors sensing and data transaction transmitting. The personal computer hosts the user interface and private Ethereum blockchain server. The private Ethereum blockchain is used to deploy smart contracts and store transaction data. ESP32-WROOM-32 micro-controllers are used to operate the peer circuits including the relays and current sensors. The prototype results show the operation of the prototype by performing the energy transfer simulation with different types of consumption loads in the determined time.
This paper addresses the continuously increasing storage demands challenge faced by blockchain networks, with a particular focus on Ethereum. We propose a novel framework that divides the network into consensus nodes, which inherit Ethereum characteristics, and storage nodes responsible for storing Merkle Patricia Trie (MPT) nodes. This design aims to reduce the storage load on individual nodes by distributing MPT nodes based on their key values. Our approach maintains network security and data integrity while easing the storage burden through a distributed storage mechanism. Key to our work is the dynamic adjustment of storage load across an expandable network of storage nodes. We validate our framework through practical experiments, involving modifications to the go-ethereum source code and testing with authentic Ethereum block data. The results confirm that our work not only mitigates storage issues but also enhances synchronization efficiency.
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.
Systems that integrate distributed databases and existing blockchain platforms have recently emerged, which conveniently leverage their respective strengths to build efficient, secure, and usable data sharing and collaboration environments for different organizations. However, the performance of such systems can be limited by the native blockchain platforms due to the high latency of transactions. In this paper, we present CoralDB, a bottom-up fully redesigned hybrid system of blockchain and database, aimed at enabling untrusted organizations to collaborate and share data efficiently and securely at the database level. The storage layer of CoralDB ensures data security and system throughput through key modules such as customized block structure, consensus mechanism, and transaction pool. On top of the storage layer, a database layer is introduced, which extends the blockchain of the storage layer by incorporating connection pools, collaborative tables, and query interfaces, to enhance the usability and efficiency of data collaboration and sharing. Extensive experimental results demonstrate that CoralDB provides security assurances at the level of blockchain and enables efficient decentralized data collaboration and sharing.
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.
Amrita Jyoti, P. K. Gupta, Sonam Gupta, Harsh Khatter · 5 authors
Ethereum is an open-source, public, blockchain-based distributed computing platform and operating system that allows the development and execution of distributed applications without the risk of downtime, fraud, control, or intervention from a third party. Along with serving as a platform, Ethereum also offers a Turing-complete Blockchain programming language that aids in the publication of distributed applications. One of the major Ethereum projects is Microsoft's collaboration with Consensus, which provides Ethereum Blockchain as a Service (EBaaS) on Microsoft Azure to give enterprise clients and developers access to a cloud-based blockchain development environment with a single click. Only the implementation determines the size of the Ethereum blockchain. Geth's Ethereum blockchain is around 11 GB in size, compared to Parity's 6 GB. Although the total size of the Ethereum blockchain, in its entirety, may reach 60GB+. Even though the toolset you require may vary depending on the specific blockchain, the majority of tools are compatible with Ethereum, therefore here we highlighted the various enhancement tools that we use for implementing blockchain applications on the Ethereum platform.
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.
Multi-dimensional performance evaluation is crucial for blockchain systems as it enables appropriate blockchain choosing for a given scenario and helps to pinpoint the bottleneck module of a blockchain system to optimize its performance. However, the existing evaluation frameworks for blockchain suffer from low system generality, inefficient workload execution, and incomprehensible evaluation metrics. In order to overcome their limitations, we design and implement the Generalized and Fine-grained Blockchain Evaluation (GFBE) framework. Specifically, we abstract 3 types of Universal Evaluation Interface (UEI) via the dynamic proxying approach to enable generalized evaluation of heterogeneous blockchain systems. Through the design of Lua-based workloads plugin with high flexibility and reusability, GFBE improves the efficiency of workload execution. To achieve comprehensive measurement, we define 15 key performance metrics across hierarchical layers of blockchain architecture. We also implement and deploy GFBE on 16 machines each with 8 CPUs and 16GB RAM, and evaluate three open-source blockchain systems namely Ethereum, ChainMaker, and Haihe smart chain. The experimental results demonstrate that GFBE efficiently and accurately measure 15 key performance metrics such as Contract Execution Efficiency at the contract layer, Consensus Agreement Time Ratio at the consensus layer, and State Query Time at the data layer. Compared with state-of-the-art frameworks such as BLOCKBENCH, Log-based, and Caliper, GFBE distinguishes itself as the only framework that encompasses the appealing features of universal interface, reusable workload, and all-layer metrics.
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.
Immutability is widely recognized as one of the blockchain’s key security attributes. However, in recent years, incidents involving the use of blockchain for disseminating illegal or malicious information have raised concerns over its strict immutability. To address these issues, redactable blockchains are proposed as a novel solution, permitting authorized content redactions without compromising the structural integrity of the blockchain. Unfortunately, current solutions are unable to restrict the abuse of redaction privilege, except for relying on a trusted authority or committee, which contradicts the trustlessness principle of blockchain. In this paper, we propose a controlled redactable blockchain protocol that allows for a limited number of redactions and supports a transparent setup. The cryptographic tools enabling this functionality are our proposed t-times chameleon hash (t-CH) and signature (t-CS) schemes, where generating more than t collisions will expose the trapdoor. We present security models, discrete logarithm-based instantiations, and formal security proofs for both t-CH and t-CS. Subsequently, we present the construction of our redaction protocol in both permissioned and permissionless settings. Finally, we experimentally demonstrate the effectiveness of the proposed protocol in practice.