An Efficient Blockchain-Based Framework For File Sharing

Blockchain is a new technology for processing complex and disordered information with respect to business and other industrial applications. This work is aimed at studying the consensus algorithm of blockchain to improve the performance of blockchain. Despite their advantages, the proof of stake (POS) algorithm and the practical Byzantine fault tolerance (PBFT) algorithm have high latency, low throughput, and poor scalability. In this paper, a blockchain hybrid consensus algorithm which combines advantages of the POS and PBFT algorithms is proposed, and the algorithm is divided into two stages: sortition and witness. The proposed algorithm reduces the number of consensus nodes to a constant value by verifiable pseudorandom sortition and performs transaction witness between nodes. The algorithm is improved and optimized from three dimensions: throughput, latency, and scalability. The experimental results show that the improved hybrid consensus algorithm is significantly superior to the previous single algorithms for its excellent scalability, high throughput, and low latency.

Blockchain technology relies on decentralized data management across various applications to ensure secure transactions. Consensus algorithms play a critical role in maintaining consistency and trust within decentralized environments, laying the groundwork for further exploration. This paper presents a simulation-based benchmarking framework for evaluating major consensus mechanisms Proof of Work (PoW), Proof of Stake (PoS), Proof of Authority (PoA), Proof of Capacity (PoC), Practical Byzantine Fault Tolerance (PBFT), Directed Acyclic Graph (DAG), and Proof of Biometric Uniqueness (PoBU). A MATLAB-based simulation environment integrated with Docker-emulated blockchain nodes was developed to measure performance across several parameters, including throughput, latency, energy consumption, finality probability, fault tolerance, and resource requirements. Results show that DAG achieves the highest throughput (1600 TPS) and lowest latency (0.8 s), while PoBU offers strong fault tolerance (50%) and energy efficiency (60 J/tx). PBFT and PoA provide ultra-fast confirmations with limited decentralization, whereas PoW demonstrate poor scalability and energy efficiency. These findings highlight the potential for a unified benchmarking framework for consensus mechanisms and provide practical insights for selecting consensus protocols for specific blockchain applications.

Blockchain technology has become one of the most disruptive innovations of the 21st century, reshaping industries such as finance, supply chain management, healthcare, and governance. However, the conventional blockchain ecosystem—particularly models based on Proof of Work (PoW)—has been widely criticized for its excessive energy consumption and ecological footprint. As societies move toward sustainability and carbon-neutral goals, the exploration of energy-efficient blockchain models becomes not just an academic pursuit but also an ethical imperative. This manuscript investigates the evolution of energy-efficient consensus mechanisms and their integration into “green smart contracts,” which enable automated, verifiable, and sustainable digital agreements. It highlights consensus algorithms such as Proof of Stake (PoS), Delegated Proof of Stake (DPoS), Proof of Authority (PoA), Proof of Space-Time (PoST), Practical Byzantine Fault Tolerance (PBFT), and emerging hybrid mechanisms. The manuscript offers a comprehensive literature review, outlines statistical insights comparing energy and performance trade-offs, and proposes methodologies for integrating eco-friendly smart contract architectures. The results emphasize that while PoW-based systems consume up to 99% more energy than PoS-based models, hybrid approaches demonstrate a promising balance between security, decentralization, and efficiency. The study concludes that energy-efficient blockchain models, when strategically aligned with sustainability frameworks, can redefine smart contract ecosystems to meet global climate commitments while maintaining reliability, transparency, and scalability.

Integration of renewable-energy (RE) sources of energy into local microgrids, decentralised energy markets using blockchain based peer-to-peer (P2P) energy trading is gaining more traction due to its ability to enable transparent, autonomous, and secure transactions among distributed energy resources (DERs). Due to the large variety in microgrid topologies and their respective operational constraints, a key challenge to obtaining the most effective trading framework is the choice of blockchain consensus protocol that suits a given microgrid type. Choice of consensus mechanism solely affects the reliability and security of a network. This paper presents a quantitative comprehensive evaluation of various blockchain consensus mechanisms such as Proof-of-Work (PoW), Proof-of-Stake (PoS), Delegated Proof-of-Stake (DPoS), Proof-of-Elapsed-Time (PoET), Practical Byzantine Fault Tolerance (PBFT), Raft, and Tendermint to determine their suitability for P2P energy trading in microgrids. Various metrics such as fault tolerance, energy efficiency, latency, throughput and consensus time were evaluated for multiple consensus mechanisms through simulations. This paper also studies node-scaling impact on the protocols and presents a final decision framework to match the suitable protocol with various microgrid topologies.

Blockchain networks use consensus mechanisms so participants can exchange transactions without the need to rely on a trusted third party. Consensus mechanisms using Proof of Work burn significant energy to select a block miner and the delay limits performance. Other consensus mechanisms such as Proof of Stake or Practical Byzantine Fault Tolerance still designate a single validator to append a block to the chain, preventing blocks from being built and published in parallel. In this paper we introduce a new consensus mechanism, Proof of Descriptor, enabling clients to work together to publish blockchain transactions using a descriptor object which stores information on the cooperative parallel execution of transactions. Proof of Descriptor consensus allows commutative transactions to be mined individually. It does not require a leader to propose the next block, enabling clients to cooperate on completing transactions, assembling blocks and publishing them. We demonstrate that our approach is less prone to attack since it is not vulnerable to a malicious leader, while simulations show a potential 20x improvement over the fastest sequential blockchain, Solana.

The challenge of collecting large scale environmental data lies in reducing the cost of allocating data sensors while improving the data quality. Compared with traditional centralized data collecting methods, obtaining environmental data by distributed "crowds" can largely reduce the cost. However, designing such crowdsourcing systems requires an appropriate incentive mechanism to encourage providing accurate and rare environmental data. In this paper, we propose to utilize blockchain-based incentive mechanisms to address the problem. We design and evaluate a blockchain-based system for large scale environmental data acquisition, which consists of a sensor layer to collect distributed environmental data, a valuation layer to evaluate the quality of the data collected, a consensus layer to incentive and motivate high quality data collection, and a ledger layer to record the incentive transactions and the qualified environmental data. The incentive mechanism in the consensus layer is achieved with a Proof-of-Data-Value (PODV) protocol adapted from the Practical Byzantine Fault Tolerance (PBFT) [11] consensus algorithm. We carry out experiments to compare the PODV with contemporary blockchain census protocols including Proof-of-Work (POW) [16] and Proof-of-Stake (POS)[18]. The experimental results show that the proposed system outperforms in encouraging crowds to provide accurate and rare environmental data, and imply that the PODV are superior in terms of throughput and environmental friendliness.

The advent of the Bitcoin system has brought another boom in the Internet era. In a very short time, many Blockchain systems come into being successively, whose decentration, consensus mechanisms, intelligent contract, and other characteristics make them applicable to various fields such as finance, education, medical, technology, etc. The consensus mechanism is the core of Blockchain technology. And a good consensus mechanism plays a very important role in the stable operation of the Blockchain system. The continuous improvement of consensus mechanisms such as PoW (proof-of-work), PoS (proof-of-stake), DPoS (delegated-proof-of-stake), and PBFT (Practical Byzantine Fault Tolerance) has led to the evolution of Blockchain technology to Blockchain 3.0. Starting from the issue of Byzantine generals, this article analyzes common consensus mechanisms based on existing Blockchain applications and then evaluates their consistency. This paper has a unique perspective, selection and comment on the latest progress and important literature in the field of block chain. At last, it also has a high degree of summary and prospect to the existing problems and the future development trend.

To mine a blockchain on IP Networks, one must do several tasks related to chain management, rule optimization, verification, and hash generation design. Various consensus model subsets may benefit from the various blockchain mining techniques proposed by researchers. Most of these techniques, however, are rather complicated, which slows down the mining process for large-scale blockchains. Overly simplistic models that include unnecessary redundancies are inefficient and have little practical use. To solve these issues and boost blockchain mining efficiency in large-scale deployments, the authors of this paper propose creating a novel hybrid bioinspired approach. The proposed IP Network model is adaptable to almost all consensus procedures and may be easily combined with dynamic consensus models with few alterations. After collecting performance and context-specific data from the underlying blockchains, the technique uses Genetic Algorithm (GA) that distributes these range sets among miner nodes that support trust, allowing for high-performance mining while maintaining a high degree of trust under actual application situations. The model was tested against Proof-of-Stake (PoS), Proof-of-Work (PoW), Proof-of-Trust (PoT), and Practical Byzantine Fault Tolerance (PBFT) based consensus algorithms to ensure its effectiveness in real-world scenarios. Mining latency, energy consumption, and computational complexity were used as metrics against which this performance was measured. This analysis revealed that the proposed model has the potential to decrease mining latency by 4.5%, energy usage by 3.9%, and compute complexity by 4.1% across a variety of consensus mechanisms, making it suitable for a number of real-time applications.

Blockchain-based audit systems use “Practical Byzantine Fault Tolerance” (PBFT) consensus protocol which suffers from a high message complexity and low scalability. Alternatives to PBFT have not been tested in blockchain-based audit systems since no blockchain testbed supports the execution and benchmarking of different consensus protocols in a unified testing environment. In this paper, we address this gap by developing a blockchain testbed capable of executing and testing five consensus protocols in a blockchain network; namely PBFT, Proof-of-Work (PoW), Proof-of-Stake (PoS), Proof-of-Elapsed Time (PoET), and Clique. We carry out performance evaluation of those consensus algorithms using data from a real-world audit system. Our results show that the Clique protocol is best suited for blockchain-based audit systems, based on scalability features.

Applying Blockchain consensus mechanisms to Network Service Federation: Analysis and performance evaluation

Cyberspace Mimic Defense (CMD) has fundamentally changed the situation of traditional network security defense through Dynamic Heterogeneous Redundancy (DHR) architecture. Presently, research on DHR architecture is based on the trustworthiness of the arbiters and schedulers. However, in practical applications, the core logic is generally deployed on a single server, which is vulnerable to single points of attack and failure, thus damaging the entire system’s security. This paper proposed a decentralized DHR architecture, which transfers the arbitration and scheduling logic to all executors. Based on the Practical Byzantine Fault Tolerance (PBFT) protocol, this paper designed the consensus protocol used in the decentralized DHR architecture to ensure the consistency of the status of each executor. Theoretical analysis and experiments show that the architecture is more secure than the traditional DHR architecture and can tolerate Byzantine faults.

Emerging peer-to-peer computing provides new possibilities but also challenges for distributed applications. Despite their significant potential, current peer-to-peer networks lack efficient knowledge discovery and management. This paper addresses this deficiency and proposes the Intelligent File Sharing framework, which provides an effective and flexible query for P2P file sharing. The IFS is based on powerful schema and flexible inference, as well as efficiently integrated and extensible retrieval algorithms. Experimental results have provided evidence of the high performance and scalability of the Intelligent File Sharing (IFS) system in peer-to-peer environments.

Background: Introducing Magnetic Levitation (Maglev) technology in a developing country is a big challenge that needs huge investments in infrastructure, operations and maintenance. Background information about the development of Maglev worldwide to date is included.
 Aim: Determine a methodology to estimate the full cost of travel and provide insights into the working model developed to include the calculations of the total social costs of building a new Maglev line for the Riyadh-Dammam corridor in Saudi Arabia and understand in what circumstances it is a suitable technology to use.
 Methods: The Spreadsheet Total Cost Model (STCM) is used to determine the calculations of operator costs, user costs, and environmental costs. However, the operator costs are related to infrastructure construction and maintenance costs, and costs associated with the acquisition, operation and maintenance of Maglev rolling stock. The user costs are dependent on the journey time, including access/egress time, waiting time, and in-vehicle time. The value of time is considered in order to get the user costs calculated. The external costs include air pollution, noise pollution, accident, and climate change per passenger-km.
 Results: The travel demand has to be forecasted in order to determine the total social costs, using the elasticity approach between the the proposed HSR and Maglev lines in terms of their number of trips and the generalised journey times. In addition, the generalised journey time is based on the in-vehicle time and service interval penalty. The Maglev system is operated at the capacity limit and the change in service is therefore forecasted to increase the Maglev demand by 24.6 % (3.25 million passengers). In terms of the total infrastructure costs, the infrastructure construction and maintenance costs are included and computed to be about € 835.4 million per year, using the capital recovery factor (0.06) based on 35 years of operation and a 5 % social discount rate. The acquiring, operating, and maintaining train’s unit cost is included in the calculation of rolling stock to achieve results of € 22.4 million, € 22.5 million, and € 40.9 million, respectively. In terms of the user costs, the access/egress time is computed as of 33 minutes, using the car, while the in-vehicle travel time and waiting time are resulted of 61.8 minutes and 7.8 minutes, respectively. The external environmental costs are based on accidents, and climate changes of € 8.87 million per year and € 8.13 million per year, respectively. However, the total social costs of Maglev line are computed as € 1.18 billion for 16.45 million passengers per year. This gives an average social cost of € 71.9 per passenger. The comparable figures for High-Speed Rail (HSR) are € 1.10 billion for 13.21 million passengers per year, giving an average social cost of € 83 per passenger.
 Conclusion: In conclusion, the Riyadh-Dammam Maglev system introduces a new intercity system into Saudi Arabia and brings new competition in the intercity transit market as a part of the future transport developments in the country. The average social cost for HSR is around 16 % higher than Maglev- but that is more proven technology.

A universal infrastructural issue is wetting of surfaces; millions of dollars are invested annually for rehabilitation and maintenance of infrastructures including roadways and buildings to fix the damages caused by moisture and frost. The biomimicry of the lotus leaf can provide superhydrophobic surfaces that can repel water droplets, thus reducing the penetration of moisture, which is linked with many deterioration mechanisms in infrastructures, such as steel corrosion, sulfate attack, alkali-aggregate reactions, and freezing and thawing. In cold-region countries, the extent of frost damage due to freezing of moisture in many components of infrastructures will be decreased significantly if water penetration can be minimized. Consequently, it will greatly reduce the maintenance and rehabilitation costs of infrastructures. The present study was conducted to explore any attempted biomimicry of the lotus leaf to produce biomimetic coatings. It focuses on anti-wetting characteristics (e.g., superhydrophobicity, sliding angle, contact angle), self-cleaning capability, durability, and some special properties (e.g., light absorbance and transmission, anti-icing capacity, anti-fouling ability) of lotus-leaf-inspired biomimetic coatings. This study also highlights the potential applications of such coatings, particularly in infrastructures. The most abundant research across coating materials showed superhydrophobicity as being well-tested while self-cleaning capacity and durability remain among the properties that require further research with existing promise. In addition, the special properties of many coating materials should be validated before practical applications.

Cloud data storage outsourcing has emerged as a service that can facilitate data owners (DOs) to store their data remotely. Outsourcing health, educational, financial, multimedia data to cloud storage server is beneficial as it eliminate the burden of initial infrastructure setup and maintenance costs. However data storage security and integrity remains challenging due to lack of control and physical possession over the data by the DOs. In this paper we present a lightweight auditing method for integrity verification and deduplication of outsourced data. The proposed scheme combines hashing and symmetric encryption with improved distributed hash table data structure which reduces the communication and computation overhead for integrity verification and also enables efficient dynamic operations of the data. The storage cost is drastically decreased by deduplication using the combined techniques of convergent encryption and filters. The outcome of the proposed methodology demonstrates that this light weight data audit protocol outperforms the other state of art schemes in computation, communication and storage costs.