A Blockchain-based Crowdsourcing System for Large Scale Environmental Data Acquisition

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 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.

Achieving good performance in terms of throughput and scalability, with high quality of security has always been a challenging problem in all sorts of scheduling. Permissioned blockchain allows multiple contracts of non-trusting peer organization to be deployed for working in consortium. It is the responsibility of the scheduler often called as an ordering service to form block of transactions to get committed through consensus. Practical Byzantine Fault Tolerance (PBFT) is one of the most popular consensus algorithm used in current implementations of blockchain. Most consensus algorithms including PBFT follow FIFO scheduling strategy to create the block of transactions. With block chain being supported for multi-contract environment, scheduling should consider difference in service requirements specifically security requirement for heterogeneous contracts. The current work proposes SAGA-PBFT (Security-Aware Genetic Algorithm based Practical Byzantine fault Tolerance) scheduler, which uses multi objective genetic algorithm for balancing the security requirement and security overhead at the time of block creations. The algorithm assigns the security level to each transaction as per its security requirement but in an unpredictable manner making security attack difficult. It further uses security aware PBFT for consensus. Experimental simulation proves that SAGA-PBFT when compared with PBFT, achieves better commit time and scalability with best possible security.

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.

The article investigates the process of block formation in blockchain networks and the impact of node network architecture and consensus algorithms on their scalability and performance. Analysis of blockchain system scalability is important due to problems that arise when network load increases, particularly the increase in the number of block forks and transaction confirmation times. The research focuses on studying the impact of network delays and the choice of consensus algorithm on the performance and scalability of blockchain networks. The main attention is devoted to mathematical models that describe block formation, as well as the analysis of factors affecting transaction processing speed and throughput. The primary consensus algorithms, such as Proof of Work (PoW) and Proof of Stake (PoS), are considered, and their impact on scalability in implementations based on the Ethereum Virtual Machine (EVM) and Bitcoin is compared. Experimental studies using Geth and Amazon cloud services revealed that the application of the Proof of Stake (PoS) consensus algorithm increases network performance by reducing the complexity of the block formation process in blockchain networks by 99% and accelerates consensus achievement by 70% compared to Proof of Work (PoW). It was also established that increasing the number of nodes from 5 to 50 reduces the network's throughput by almost 10%, and the average confirmation time doubles. The obtained results are aimed at solving the scalability issue by reducing transaction confirmation times for the implementation of decentralized technologies in the Internet of Things (IoT) sphere, where processing speed and storage of large volumes of data are critically important. Keywords: blockchain, block formation, consensus algorithms, decentralized technologies, Ethereum Virtual Machine (EVM), Internet of Things (IoT), mathematical modeling, network delays, scalability.

This research document demonstrates the understanding of two key elements: Proof of Work (PoW) and Proof of Stake (PoS) within cryptocurrency. Cryptocurrency is often misunderstood as just volatile and risky but many investors do not understand what it even is. What is proof of work (BTC)? What is proof of stake (ETH)? How are they similar and how are they different? Cryptocurrency is actually more relatable that originally imagined once a person understands digital currency, money, it’s origins, and how they hold similar monetary value within their own wallets. Cryptocurrency in PoW involves complicated mathematical equation solving via mining from a large growing pool of miners. These miners receive rewards such as bitcoin/tokens/etc. from their mined hash blocks verified, and blocks added to the blockchain. Challenges are that there are many miners and there may be a computational limit per core of each PC to be able to mine since Bitcoin has increased its difficulty 70 billion times since it started. BTC or Bitcoin is still widely trusted due to its increasing difficulty to race to the finish line to finish the advanced math computations. Whereas within PoS this is not a race between the masses and advanced math computations, but a validator that generally has more put in their stake vs. gained by receiving the processing fees associated. ETH or Ethereum has shifted from PoW to PoS for its better energy efficiency in resources. It has employed many other additional checks from Casper to Gasper which is the combination of Casper (fork-choice algorithm), LMD-GHOST (heavest observed subtree), and finality which requires 2/3rd agreement as well as once a block is justified it is upgraded to a finalized block. the similarities between the two PoW and PoS are that they are consensus-driven algorithms. They are designed to reach an agreement between the systems in place before each block is placed in the blockchain. Additionally, they also have a shared public ledger that operates on a global if not international scale. With blockchains, there is always only one true version and this is relying on a network rather than a governing authority like a bank/government entity to provide security and to prevent fraudulent transactions. It is still widely contested which is better than these two well-known consensus algorithms and it is still widely contested. The best answer is suited on a per investor per business basis in terms of the willingness of taking a risk just like any investment. This document serves to help provide guidance in the understanding of cryptocurrency of two main consensus algorithms, its similarities, differences, and help identify see what a potential investor the reader may be.

Cryptocurrencies have seen a massive surge in popularity and behind these new virtual currencies is an innovative technology called the blockchain: a distributed digital ledger in which cryptocurrency transactions are recorded after having been verified. The transactions within a ledger are verified by multiple clients or “validators,” within the cryptocurrency's peer-to-peer network using one of many varied consensus algorithms for resolving the problem of reliability in a network involving multiple unreliable nodes. The most widely used consensus algorithms are the Proof of Work (PoW) algorithm and the Proof of Stake (PoS) algorithm; however, there are also other consensus algorithms which utilize alternative implementations of PoW and PoS, as well as other hybrid implementations and some altogether new consensus strategies. In this paper, we perform a comparative analysis of typical consensus algorithms and some of their contemporaries that are currently in use in modern blockchains. Our analysis focuses on the algorithmic steps taken by each consensus algorithm, the scalability of the algorithm, the method the algorithm rewards validators for their time spent verifying blocks, and the security risks present within the algorithm. Finally, we present our conclusion and some possible future trends for consensus algorithms used in blockchains.

Healthcare Blockchains (HBC) are grooming nowadays due to the requirements of flexible Electronic Health Records (EHR) management, privacy needs, and controlled medical data access. Blockchain technology very much suits these requirements and support in various healthcare data access control methods. More focus on improved block generation time gives the expected blockchain performance. Block generation time can be significantly improved by the consensus algorithms used by the system. Traditional consensus algorithm of Proof of Work (PoW) and Proof of Stake (PoS) require heavy computational resources and hence by computational overheads. The proposed system introduces a new privacy-preserving HBC consensus protocol as a consequence of member attribute values and significantly reduced computational resources. The new attribute-based consensus algorithm for HBC called Proof of Policy (PoP) is constructed using Attribute-Based Ring Signature (ABRS). This signature agrees on the stake of attribute-based ring membership and can be considered as an extension of Proof of Stake (PoS). It is also found that the proposed PoP consensus algorithm requires less computational resources than popular PoW and PoS.

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.

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.

Practical Byzantine Fault Tolerance (PBFT) is a deterministic consensus algorithm, which is widely used in blockchain due to the advantage of no forks. However, PBFT still has some problems, such as not being suitable for dynamic networks, requiring large communication overhead, and not being able to identify Byzantine nodes. Therefore, we propose Extensible-PBFT (EPBFT) consensus algorithm, it can take different steps to reach consensus according to the network environment of the system. Firstly, we add the election of consensus nodes based on verifiable random function (VRF), which makes EPBFT suitable for dynamic networks. Then, we modify the consistency protocol so that EPBFT can reach consensus with less communication in a stable network, and it can also identify Byzantine nodes and reduce confirmation latency. Finally, we simplify the checkpoint protocol and the view-change protocol, reducing the time and communication overhead they require.

DTPBFT:A dynamic and highly trusted blockchain consensus algorithm for UAV swarm

Data collection and analysis is vital for evaluating the performance of any equipment or system. Though the methodology of collection, transmission, storage and retrieval varies in different scenarios, the basic components of the set-up remain the same. The Data Acquisition and Monitoring System evolved from the need for remote monitoring of facilities that did not have an independent reliable infrastructure to implement a full-fledged SCADA system. Back when IT infrastructure was prioritized for business communications within the limited bandwidth allocated, collection and transmission of process data through the available network infrastructure was a challenge. More so when there are concerns regarding the confidentiality of data being collected and transmitted. Individual facilities were provided with local instrumentation and controls for reliable operations. With the growing production rates, the focus generally goes for improving the processing facilities rather than reading, reporting or recording. Instead of an independent dedicated network for Supervisory Control and Data Acquisition system that mandate a huge infrastructural cost and dedicated skilled personnel, a pilot project was initiated with a minimum budget to test data transfer through existing communication network. Field transmitters were installed on Wellheads, Risers and Manifolds and Remote Terminal Units were provided to collect data from two platforms and to facilitate data transfer to the servers through existing microwave communication network with minimum field instrumentation. Considering bandwidth limitations and priority for business communications, servers in redundant configuration were placed strategically to ensure continuous data gathering. Pilot project was successful in providing reliable data and trends with minimum disruptions. Augmentation of DAMS network was envisioned to implement Digital Oil Field for monitoring multiple assets in real time. Implementation of Digital Oil Field continued with the addition of new field instrumentation and RTUs followed by server upgrades and integration of PLC based platform control systems to add four major producing platforms to the Data Acquisition and Monitoring System through existing microwave communication network. Upon successful commissioning, it was possible to gather data from various wellheads, process equipment and other independent meters for remote real time monitoring and analysis through user friendly HMI screens and customized dashboards to manage multiple assets effectively, improving performance evaluation, safety and reliability of operations.

The Practical Byzantine Fault-Tolerant (PBFT) consensus algorithm faces challenges such as random master node selection, high communication overhead, and a lack of incentive and penalty mechanisms, which undermine its efficiency and security in large-scale network environments. To address these issues, this paper proposes an improved PBFT consensus algorithm, RF-PBFT, which integrates a random forest-based node grouping mechanism with a dynamic reputation system. The algorithm leverages key behavioral data of nodes during the consensus process to train a random forest model, partitioning nodes into a consensus set and a candidate set. Nodes with superior predictive performance are selected to participate in the consensus process, thereby reducing redundant communication overhead. Furthermore, a differentiated reputation mechanism is established for the consensus group and the candidate group to encourage positive behavior and deter malicious actions. The master node is elected through a combination of prediction results and voting, enhancing system reliability and security. Simulation results demonstrate that, compared with traditional PBFT and other state-of-the-art variants, RF-PBFT significantly reduces communication overhead, decreases consensus latency, and improves throughput, validating its effectiveness in multi-node blockchain systems.