FIGURE 1 - available via license: Creative Commons Attribution 4.0 International
Content may be subject to copyright.
Source publication
The rapid development of blockchain technology and their numerous emerging applications have received huge attention in recent years. The distributed consensus mechanism is the backbone of a blockchain network. It plays a key role in ensuring the network, s security, integrity, and performance. Most current blockchain networks have been deploying t...
Context in source publication
Context 1
... illustrated in Fig. 1, in the blockchain, transactions (data) are stored in blocks which form an ever-growing sequence (chain) shared among participants in the network. Transactions are the fundamental units of a blockchain. For example, when Alice wants to send money to Bob, she creates a transaction which consists of her address as the input, her digital ...
Similar publications
This work provides a short but technical introduction to the main building blocks of a blockchain. It argues that a blockchain is not a revolutionary technology but rather a clever combination of three fields: cryptography, decentralization and game theory. In addition, it summaries the differences between a public, private and federate blockchain...
Citations
... With Ethereum's transition to Proof-of-Stake (PoS), validators now propose and attest to blocks [15]. However, mempool congestion and transaction prioritization strategies can delay block finalization. ...
Ethereum's transaction pool (mempool) dynamics and fee market efficiency critically affect transaction inclusion, validator workload, and overall network performance. This research empirically analyzes gas price variations, mempool clearance rates, and block finalization times in Ethereum's proof-of-stake ecosystem using real-time data from Geth and Prysm nodes. We observe that high-fee transactions are consistently prioritized, while low-fee transactions face delays or exclusion despite EIP-1559's intended improvements. Mempool congestion remains a key factor in validator efficiency and proposal latency. We provide empirical evidence of persistent fee-based disparities and show that extremely high fees do not always guarantee faster confirmation, revealing inefficiencies in the current fee market. To address these issues, we propose congestion-aware fee adjustments, reserved block slots for low-fee transactions, and improved handling of out-of-gas vulnerabilities. By mitigating prioritization bias and execution inefficiencies, our findings support more equitable transaction inclusion, enhance validator performance, and promote scalability. This work contributes to Ethereum's long-term decentralization by reducing dependence on high transaction fees for network participation.
... It is a very complex method that requires a huge amount of energy. Another consensus method is Proof of Stake (PoS) [45]. Unlike PoW, which relies on computational power, PoS selects validators based on the number of tokens they hold and are willing to "stake" as collateral. ...
In recent years, Facility Management has undergone significant technological and methodological advancements, primarily driven by Building Information Modelling (BIM), Computer-Aided Facility Management (CAFM), and Computerized Maintenance Management Systems (CMMS). These innovations have improved process efficiency and risk management. However, challenges remain in asset management, maintenance, traceability, and transparency. This study investigates the potential of blockchain technology and non-fungible tokens (NFTs) to address these challenges. By referencing international (ISO, BOMA) and European (EN) standards, the research develops an asset management process model incorporating blockchain and NFTs. The methodology includes evaluating the technical and practical aspects of this model and strategies for metadata utilization. The model ensures an immutable record of transactions and maintenance activities, reducing errors and fraud. Smart contracts automate sub-phases like progress validation and milestone-based payments, increasing operational efficiency. The study’s practical implications are significant, offering advanced solutions for transparent, efficient, and secure Facility Management. It lays the groundwork for future research, emphasizing practical implementations and real-world case studies. Additionally, integrating blockchain with emerging technologies like artificial intelligence and machine learning could further enhance Facility Management processes.
... For example, in Proof-of-Work (PoW) algorithms [10], nodes compete to solve a cryptographic puzzle, with the winner adding the next block. In Proof-of-Stake (PoS) algorithms [16], nodes are selected based on the amount of stake they hold in the network, with higher stakes increasing the likelihood of selection. As already mentioned, in this work we integrate a novel hybrid consensus algorithm to HLF. ...
... The third consensus if Proof of Knowledge (PoK) (68), a better version of PoK is Zeroknowledge Proof (ZKP) [66]. In this method, one party (Prover) can prove that a specific statement is true to the other party (verifier) without disclosing any additional information. ...
The aim of the paper is to perform a bibliometric study on blockchain which is an emerging technology presenting several advantages reinforcing security, privacy and immutability on a Peer-To-Peer network, inhibiting a central authority like a server. The studied articles are collected from the Clarivate Analytics Web of Science Core Collection database (data updated on 29 June 2023). A total of 11,190 blockchain documents were searched out in the SCI-EXPANDED from 1991 to 2022. The articles are analysed using characteristics of document types. The most used type is articles and reviews, relevant review articles, average numbers of citations per publication by year. The most cited publications are those published in 1991. The most cited Web of Science categories are “information systems computer science” and “electrical and electronic engineering”. The top most productive journals are IEEE journals and the top productive countries are China, USA and India. The top productive institutions are Beijing University of Posts and Telecommunications, Chinese Academy of Sciences, Xidian University. The top ten most frequently cited blockchain articles and the twenty most frequently used author keywords are exhibited to deduce trends of research in blockchain field. The contribution to the literature is reinforced by the given summary about the blockchain technology since 1991 and its developments, its actual shape and its trends toward the future.
... By integrating blockchain technology, this layer eliminates intermediaries, and enhances security and trust in IoT ecosystems [81]. The incorporation of consensus mechanisms, such as Proof of Work (PoW), Proof of Stake (PoS), and Delegated Proof of Stake (DPoS), ensures consistent agreement across network participants regarding transaction validity and ledger state, playing a critical role in preventing fraud and maintaining data integrity [99]. -Middleware layer: The middleware layer is essential in a decentralized IoT marketplace architecture, serving as the glue that binds together different components of the system. ...
Service discovery matchmaking plays a vital role in the cyber marketplace for the Internet of Things (IoT), especially in peer-to-peer environments where buyers and sellers dynamically register and match resource profiles online. As the IoT marketplace expands, efficient resource allocation through matchmaking is increasingly important. However, the growing complexity of service discovery, coupled with data security and privacy challenges, complicates the identification of suitable services. To address these issues, this study conducts a comprehensive review of matchmaking algorithms within the IoT marketplace by examining their key attributes, strengths, and limitations as documented in academic literature. This paper categorizes and summarizes state-of-the-art approaches, identifying research gaps and proposing future directions. Our comparative analysis highlights the strengths and weaknesses of current methodologies, advocating for deep learning and context-aware solutions to improve service efficiency. Additionally, blockchain-based approaches are discussed for their potential to improve security, trust, and privacy-preserving transactions. This research lays a critical foundation for the advancement of secure, efficient IoT-enabled marketplaces.
... Computation complexity denotes the computation time required for block generation. Many DLTs adopt puzzle-based mechanisms like Proof-of-Work (PoW) [19] and Proof-of-Stake (PoS) [20], demanding substantial computational resources. Implementing privacy features into such block creation or block propagation processes using privacy-preserving mechanisms invariably escalates computational and communication overhead respectively. ...
Directed Acyclic Graph (DAG)-based Distributed Ledger Technologies (DLTs) have emerged as a promising solution to the scalability issues inherent in traditional blockchains. However, amidst the focus on scalability, the crucial aspect of privacy within DAG-based DLTs has been largely overlooked. This paper seeks to address this gap by providing a comprehensive examination of privacy notions and challenges within DAG-based DLTs. We delve into potential methodologies to enhance privacy within these systems, while also analyzing the associated hurdles and real-world implementations within state-of-the-art DAG-based DLTs. By exploring these methodologies, we not only illuminate the current landscape of privacy in DAG-based DLTs but also outline future research directions in this evolving field.
... One of the most persistent bottlenecks in transaction throughput has concerned PoW-based networks, of which Bitcoin is a part [1], [2]. The nature of mining, both energy-consuming and intensive in computation to validate blocks, limits the number of transactions possible per second, aside from causing excessive energy use [29], [30], [31], [32]. While PoW ensures high security and decentralization, the low efficiency and environmental impacts this consensus methodology has brought forward, for many, have begun the search for alternative consensus mechanisms to enable high-throughput blockchain applications. ...
... Comparison of (a) Proof-of-Work and (b) Proof-of-Stake mechanisms[29]. ...
This paper introduces the Proof-of-Diversity (PoD) protocol, a new consensus mechanism that enhances decentralization, security, and energy efficiency using demographic, geographic, and computational diversity in validator selection. By using a multi-dimensional entropy-based approach, PoD shows high resistance to Sybil attacks, fosters inclusion, and ensures fair participation. Comparative analysis with Tendermint Proof-of-Stake (PoS) and Algorand Proof-of-Stake (Algorand) shows that PoD is more effective in various key metrics, including transaction finality, validator engagement, diversity entropy, energy use, and adaptability. In particular, PoD achieves a shortest average transaction finality time of 72.84 ms over a given period, a notable improvement compared to both Algorand at 215.37 ms and Tendermint PoS at 278.42 ms. In addition, PoD achieves a validator engagement of 85.42%, strengthening its ability to maintain decentralization. PoD also achieves a diversity score of 0.79, better than Tendermint PoS and Algorand, indicating a more fair and inclusive validator selection process. In terms of energy use, PoD achieves a mere 0.0132 kWh per transaction per second (TPS), a considerable improvement compared to its counterparts. In addition, PoD shows better adaptability to changes in step parameters and changes in benefit-cost ratios, further improving validator selection and network optimization. Overall, these results make PoD a scalable and sustainable consensus system that balances diversity, security, and performance in blockchain networks.
... In PoS, validators are chosen based on the number of tokens they hold and are willing to "stake" as collateral [20] [31]. Validators are selected randomly to propose and validate blocks, eliminating the need for energy-intensive mining [17] [95]. The energy consumption of PoS can be calculated using Eq. ...
Blockchain technology offers promise for decentralization and transparency, yet faces increasing scrutiny due to the high energy consumption of consensus mechanisms like Proof-of-Work (PoW). This systematic literature review evaluates the energy efficiency of eight major mechanisms—PoW, Proof-of-Stake (PoS), Delegated PoS (DPoS), Proof-of-Authority (PoA), Proof-of-Space (PoSpace), Directed Acyclic Graphs (DAGs), Byzantine Fault Tolerance (BFT), and Proof-of-History (PoH)—along with architectural innovations such as sharding, rollups, and hybrid models. Drawing from 53 peer-reviewed studies and industry reports (2018–2024), the review synthesizes empirical energy metrics (e.g., kWh/transaction, TWh/year), explores scalability-energy trade-offs, and identifies technical and regulatory barriers. Findings show PoS and DAGs reduce energy use by over 99% compared to PoW, though potential compromises in decentralization and security remain. Architectural enhancements like Layer-2 scaling and modular designs improve energy efficiency but increase system complexity. Regulatory frameworks such as the EU’s MiCA and the Crypto Climate Accord promote renewable integration and call for standardized energy metrics. This study offers practical insights for developers, policymakers, and enterprises, and proposes future research into quantum-resistant protocols and decentralized energy solutions. It concludes that blockchain can support global climate goals through interdisciplinary innovation and sustainable governance.
... PoS-based systems often exhibit wealth accumulation effects [11], leading to concerns about long-term decentralization. Simulationbased studies on PoS fairness [12] and validator behavior [13] indicate that even non-PoW mechanisms can exhibit centralization tendencies. PoTS addresses these concerns by ensuring that rewards are distributed among all team members, mitigating dominance by high-performance nodes. ...
This paper presents an empirical evaluation of the Proof of Team Sprint (PoTS) consensus algorithm, focusing on reward fairness, energy efficiency, system stability, and scalability. We conducted large-scale simulations comparing PoTS with conventional Proof of Work (PoW) across various team sizes and computational conditions. In PoW, the highest-performance node ranked first in all 100 trials, demonstrating extreme centralization. In contrast, PoTS reduced this dominance: the same node ranked first only 54 times, indicating fairer reward distribution. Statistical analysis showed that as team size increased, skewness and kurtosis of reward distributions decreased, confirming improved equity among participants. PoTS also demonstrated significant energy savings. The total active computation time followed a near 1/N scaling trend, reducing energy use by up to 64 times when team size was 64, while preserving consensus integrity. Repeated simulations showed stable reward distributions and system performance, affirming PoTS's robustness. Furthermore, the correlation between performance and reward peaked at 0.90 for team size 16, reflecting an optimal balance between fairness and meritocracy. Overall, PoTS offers a cooperative, energy-efficient alternative to PoW, mitigating centralization risks and promoting equitable participation. These findings validate PoTS as a sustainable and fair consensus mechanism suited for future blockchain systems.
... By integrating blockchain technology, this layer eliminates intermediaries, and enhances security and trust in IoT ecosystems [81]. The incorporation of consensus mechanisms, such as Proof of Work (PoW), Proof of Stake (PoS), and Delegated Proof of Stake (DPoS), ensures consistent agreement across network participants regarding transaction validity and ledger state, playing a critical role in preventing fraud and maintaining data integrity [99]. -Middleware layer: The middleware layer is essential in a decentralized IoT marketplace architecture, serving as the glue that binds together different components of the system. ...
Service discovery matchmaking plays a vital role in the cyber marketplace for the Internet of Things (IoT), especially in peer-to-peer environments where buyers and sellers dynamically register and match resource profiles online. As the IoT marketplace expands, efficient resource allocation through matchmaking is increasingly important. However, the growing complexity of service discovery, coupled with data security and privacy challenges, complicates the identification of suitable services. To address these issues, this study conducts a comprehensive review of matchmaking algorithms within the IoT marketplace by examining their key attributes, strengths, and limitations as documented in academic literature. This paper categorizes and summarizes state-of-the-art approaches, identifying research gaps and proposing future directions. Our comparative analysis highlights the strengths and weaknesses of current methodologies, advocating for deep learning and context-aware solutions to improve service efficiency. Additionally, blockchain-based approaches are discussed for their potential to improve security, trust, and privacy-preserving transactions. This research lays a critical foundation for the advancement of secure, efficient IoT-enabled marketplaces.
