Suman Bunia, Owen Campbell, Arthur Carvalho, Vamsi Alluri
The healthcare transport sector has progressed considerably in recent years, yet it continues to face persistent challenges such as payment, staffing, record redundancy, and resource waste. This paper proposes a blockchain-based auction system called Smart Contract enabled Fair, Secure, and Transparent Auction (SCeFSTA) that aims to address these problems and provide fair competition for healthcare transportation. SCeFSTA employs blockchain technology to create a transparent and secure auction-based platform that provides secure, immediate payment for services and promotes competition. It allows healthcare transportation providers to bid for services, ensuring that only cost-effective providers are selected. The smart contract ensures payments are made upon service completion, enhancing security for patients and providers. We follow a design science research approach to design the system after interviewing several key stakeholders in the healthcare transportation community. The blockchain-based data ledger reduces redundancy and waste while providing enhanced privacy and security. SCeFSTA has the potential to benefit the healthcare transportation field by creating a fair and efficient system that improves performance. We demonstrated the prototype to the first responder community, who understood the effectiveness. Through a series of rigorous system evaluations, we demonstrate that the proposed system could be deployed to healthcare transportation such as ambulance hire, and inter-facility patient transfer.
Proof-of-stake (PoS) has emerged as a natural alternative to the resource-intensive Proof-of-Work (PoW) blockchain, as was recently seen with the Ethereum Merge. PoS-based blockchains require an initial stake distribution among the participants. Typically, this initial stake distribution is called bootstrapping. This paper argues that existing bootstrapping protocols are prone to centralization. To address centralization due to bootstrapping, we propose a novel game $Γ_\textsf{bootstrap}$. Next, we define three conditions: (i) Individual Rationality (IR), (ii) Incentive Compatibility (IC), and (iii) $(τ,δ,ε)-$ Decentralization that an \emph{ideal} bootstrapping protocol must satisfy. $(τ,δ,ε)$ are certain parameters to quantify decentralization. Towards this, we propose a novel centralization metric, C-NORM, to measure centralization in a PoS System. We define a centralization game -- $Γ_\textsf{cent}$, to analyze the efficacy of centralization metrics. We show that C-NORM effectively captures centralization in the presence of strategic players capable of launching Sybil attacks. With C-NORM, we analyze popular bootstrapping protocols such as Airdrop and Proof-of-Burn (PoB) and prove that they do not satisfy IC and IR, respectively. Motivated by the Ethereum Merge, we study W2SB (a PoW-based bootstrapping protocol) and prove it is ideal. In addition, we conduct synthetic simulations to empirically validate that W2SB bootstrapped PoS is decentralized.
Blockchain is a secure database shared across a network of all participants, characterised by immutability, openness, transparency, and traceability. Therefore, blockchain technology is widely used in supply chain management, which can increase consumers' understanding of product information when goods arrive at the consumer end and increase the risk of consumer privacy information leakage. Considering a supply chain system that consists of a manufacturer and a platform, this paper studies the strategic interactions between the platform's adoption of blockchain technology and the manufacturer's product line design based on blockchain's positive and negative impacts on consumers. We examine the driving factors of the platform's use of blockchain technology, which are related to the effect of information transparency and privacy concerns caused by blockchain and the marginal production cost coefficient. In particular, a higher marginal production cost coefficient could make the platform more likely to use blockchain technology. We also find that the practice of blockchain technology may incentivize a manufacturer to extend its product line.
Zero-knowledge proofs (ZKPs) are computationally demanding to generate. Their importance for applications like ZK-Rollups has prompted some to outsource ZKP generation to a market of specialized provers. However, existing market designs either do not fit the ZKP setting or lack formal description and analysis. In this work, we propose a formal ZKP market model that captures the interactions between users submitting ZKP tasks and provers competing to generate proofs. Building on this model, we introduce $Prooφ$, an auction-based ZKP market mechanism. We prove that $Prooφ$ is incentive compatible for users and provers, and budget balanced. We augment $Prooφ$ with system-level designs to address the practical challenges of our setting, such as Sybil attacks, misreporting of prover capacity, and collusion. We analyze our system-level designs and show how they can mitigate the various security concerns.
The Internet of Vehicles (IoV) has a significant impact on improving traffic efficiency and driving safety. In this paper, we propose an intelligent transportation credit system based on blockchain, and design a crossroad passing smart contract that allows time-sensitive convoys to pass a crossroad earlier by paying traffic tokens for right-of-way trade. Second, this paper formulates the time–cost optimization problem under the premise of protecting the privacy of preceding convoys. Based on game theory with incomplete information, two right-of-way optimal bid strategies are given. Both theoretical analysis and simulation prove that the strategy proposed in this paper effectively reduces the waiting time of time-sensitive vehicles at a crossroad and increases the trade success probability, which, in turn, improves the expected total profit of convoys and achieves Pareto improvement.
In the twenty-first century, climate change and global warming present enormous difficulties that call for creative solutions to deal with rising greenhouse gas emissions. The Kyoto Protocol established a framework for lowering these emissions by establishing a carbon trading system in recognition of the possibilities of an international market system. The necessity for a more reliable and effective strategy was highlighted by the fact that earlier attempts faced severe obstacles such fragmented implementation, problems with transparency, high transaction costs, and worries about over-crediting. In response, our research attempts to create a revolutionary solution by developing a Carbon Credit Ecosystem with the use of smart contracts and state-of-the-art blockchain technology. By improving market consistency, liquidity, accessibility, and transparency in the carbon domain, this ground-breaking project aims to avoid the mistakes of the past.
Shovon Das Chowdhury, Tanjil Ahmed, Ruhul Amin, Rahat Ahmed Chowdhury · 6 authors
The escalating growth in population has led to a substantial increase in both private and public transportation on roads. Consequently, the surge in accidents, traffic rule violations, and other traffic-related offenses has become a daily concern. Addressing these issues is crucial for ensuring the safety of passengers and enhancing transparency in driver recruitment, especially when considering violations that may have occurred abroad. This paper introduces S- DrivingRecords, focusing on pivotal functionalities such as the registration of cases related to traffic rule violations or accidents, case withdrawal, and the sharing of driver history with external Decentralized Applications (DApps). The system facilitates case registration through a dedicated traffic DApp, enabling drivers to share their records with other entities, be they companies or individuals. This feature allows individuals to conduct thorough checks on a driver's history before making decisions such as hiring or booking. The implementation employs Hyperledger Fabric as a distributed ledger to ensure the security of data, while the use of Hyperledger Cacti facilitates seamless collaboration with different systems.
As the potential of directed acyclic graph (DAG)-based distributed ledgers in IoT systems unfolds, a need arises to understand their intricate dynamics in real-world scenarios. It is well known that discrete event simulations can provide high-fidelity evaluations of protocols. However, there is a lack of public discrete event simulators capable of assessing DAG-based distributed ledgers. In this paper, a discrete-event-based distributed ledger simulator is introduced, with which we investigate a custom Python-based implementation of IOTA's Tangle DAG protocol. The study reveals the dynamics of Tangle (particularly Poisson processes in transaction dynamics), the efficiency and intricacies of the random walk in Tangle, and the quantitative assessment of node convergence. Furthermore, the research underscores the significance of weight updates without depth limitations and provides insights into the role, challenges, and implications of the coordinator/validator in DAG architectures. The results are striking, and although the findings are reported only for Tangle, they demonstrate the need for adaptable and versatile discrete event simulators for DAG architectures and tip selection methodologies in general.
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.
The DLT Regulation aims to introduce a pilot regime for the practical application of distributed ledger technology (DLT) in post-trade services. The DLT Regulation seeks to provide a regulatory framework for the development of DLT multilateral trading facilities (DLT MTFs) and DLT securities settlement systems (DLT SSS), including for the granting and withdrawal of specific permissions (that is, permissions granted under this new regulation would allow market participants to operate a DLT market infrastructure and provide their services across all Member States). It aims at providing a mechanism, procedures and rules for allowing market infrastructures to experiment DLT with legal certainty and flexibility.
J. R. Arunkumar, M Aswathy, Rohit Mathew Samuel, Sai Shibu N B
The issue of traffic congestion and air pollution has emerged as a significant concern in contemporary metropolitan regions, demanding the implementation of inventive measures to mitigate these problems. Ride-sharing or Carpooling has emerged as a promising strategy to mitigate excessive traffic congestion while decreasing the per capita carbon footprint. Nevertheless, traditional carpooling systems have notable security and privacy concerns, such as susceptibility to cyber threats and the potential for car owners or carpooling platforms to exploit data. This paper presents a novel approach by incorporating blockchain technology into the carpooling network. Blockchain technology presents a resilient alternative for augmenting security and ensuring data integrity within ridesharing networks since it operates as a decentralised and tamperproof ledger. Additionally, it facilitates the optimisation of ride-sharing operations and the implementation of cost-sharing mechanisms via Smart Contracts. The paper outlines the smart contracts developed to enrol clients and drivers on the platform, facilitate ride-sharing, manage payments, and collect feedback. Additionally, a performance assessment was conducted on the efficacy of the aforementioned smart contract, and a thorough analysis of the outcomes was undertaken.
Purpose Presently, existing electric car sharing platforms are based on a centralized architecture which are faced with inadequate trust and pricing issues as these platforms requires an intermediary to maintain users’ data and handle transactions between participants. Therefore, this article aims to develop a decentralized peer-to-peer electric car sharing prototype framework that offers trustable and cost transparency. Design/methodology/approach This study employs a systematic review and data were collected from the literature and existing technical report documents after which content analysis is carried out to identify current problems and state-of-the-art electric car sharing. A use case scenario was then presented to preliminarily validate and show how the developed prototype framework addresses the trust-lessness in electric car sharing via distributed ledger technologies (DLTs). Findings Findings from this study present a use case scenario that depicts how businesses can design and implement a distributed peer-to-peer electric car sharing platforms based on IOTA technology, smart contracts and IOTA eWallet. Main findings from this study unlock the tremendous potential of DLT to foster sustainable road transportation. By employing a token-based approach this study enables electric car sharing that promotes sustainable road transportation. Practical implications Practically the developed decentralized prototype framework provides improved cost transparency and fairness guarantees as it is not based on a centralized price management system. The DLT based decentralized prototype framework aids to orchestrate the incentivize monetization and rewarding mechanisms among participants that share their electric cars enabling them to collaborate towards lessening CO 2 emissions. Social implications The findings advocate that electric vehicle sharing has become an essential component of sustainable road transportation by increasing electric car utilization and decreasing the number of vehicles on the road. Originality/value The key novelty of the article is introducing a decentralized prototype framework to be employed to develop an electric car sharing solution without a central control or governance, which improves cost transparency. As compared to prior centralized platforms, the prototype framework employs IOTA technology smart contracts and IOTA eWallet to improve mobility related services.
Yuzheng Ren, Renchao Xie, F. Richard Yu, Ran Zhang · 7 authors
“Read-write-own” based Web3 has been proposed as a promising user-centric Internet to open the new generation of the World Wide Web, where Web3 users can independently manage data and derive value from creating content without relying on intermediaries. Connected and autonomous vehicles (CAVs) in Web3 can trade models in a self-controlled and decentralized credible way, which is a fundamentally and principally innovation based on novel architecture. Effectively implementing such paradigms involves proper model trading strategies. However, reinforcement learning (RL)-based strategies face challenges of poor generalization ability, low feasibility, and the exploration-exploitation dilemma. It is also difficult to define an explicit and appropriate reward function. Therefore, in this paper, we propose an intelligence-based reinforcement learning (IRL) approach for CAVs in Web3. We present a framework to enable model transactions between CAVs. Also, we provide a decentralized identifier (DID)-based identity management system for resource description and data verification to access Web3, followed by the mechanism and supporting smart contracts. Furthermore, we formulate the model trading issue as an active inference to form higher-level cognition about the environment without rewards. Then we use IRL to solve it. And we use “intelligence”, a high-level indicator, to quantify the efficiency of such cognition. It can evaluate the difference between the predicted state and the real state in policy exploration. The proposed scheme shows good generalization and can auto-balance exploration and exploitation, simultaneously achieving outperforming performance on the model trading issue with no rewards. In simulations, the performance of the proposed scheme is compared with existing methods.
With the development of Electric Vehicles (EVs), Vehicle-to-Vehicle (V2V) electricity transactions have gained popularity. Among them, EV users can easily obtain information such as their own location and speed through the Internet of Vehicles (IoV), and communicate with other entities through the IoV, but the leak of the electricity transaction plan and private information such as identity, location, speed, etc. required for the transaction may put the users in danger and undermine the fairness of the transaction. Aiming at the above problems, A V2V electricity transaction scheme with privacy protection based on the IoV and consortium blockchain is proposed. Firstly, a long-term and short-term pseudo-identity algorithm is designed for users participating in V2V transactions. Users conduct each electricity transaction with different short-term pseudo-identities to prevent the leakage of their identity information; and when fraudulent transactions occur, the real identity of the fraudulent users can be traced based on their long-term pseudo-identities or public key information. Secondly, a certificateless aggregate signcryption algorithm is designed for secure communication in the IoV. Finally, consortium blockchain technology is adopted to solve the problems of single point of failure and data tampering that exist in centralized transactions. At the same time, a reputation value evaluation mechanism based on transaction completion rate and a Proof of Reputation consensus mechanism based on fixed time and fixed block capacity packing method are also designed, which not only reduces the computational power consumption but also motivates the seller EV to conduct V2V electricity transactions in good faith. The theory proves that the scheme is capable of protecting the privacy of EV users effectively. The performance evaluations demonstrate that this scheme has low communication overhead and the computational overhead also has certain advantages.
Prateek Sethi, Tri Nguyen, Mayukh Roy Chowdhury, Susanna Pirttikangas · 5 authors
Blockchain technology relies on Peer-to-Peer (P2P) ledgers that require a mechanism to maintain security and ensure consensus. The Proof of Work (PoW) consensus algorithm requires participants to dedicate significant computation to solve a cryptography puzzle. The Proof of Work Difficulty (PoW-D) in large public blockchains, such as Ethereum, is adjusted based on the time taken by the winning miner to mine the last block since the system is unaware of the computation power in the blockchain. The consortium and private blockchains provide greater visibility of the nodes involved, which may have variable compute power over time. Such heterogeneity in miners makes it challenging to maintain fairness leading to super linear profits. To address these issues, we propose two novel Reinforcement Learning (RL)-based techniques to intelligently select miners and adaptively update the PoW-D based on the variable compute power of the heterogeneous miners - RL based Miner Selection (RL-MS) and RL based Miner and Difficulty Selection (RL-MDS). Compared to the existing PoW techniques, the proposed approach lowered the winning percentage of the miners below a fairness factor threshold. Furthermore, the block mining time constraint violation is significantly reduced by up to 97% and up to 85% in RL-MS and RL-MDS, respectively.
Yuxiao Liang, Zhishang Wang, Abderazek Ben Abdallah
In the present era, energy issues are a significant concern, and the energy trading market is the crucial sector to facilitate supply-demand balance and sustainable development. For better demand response and grid balancing, vehicle-to-grid (V2G) technology is rapidly gaining importance in energy markets. To narrow the gap between ideal V2G goals and actual applications needs, energy trading system has to overcome the challenges of over-centralized structure, inflexible timeline adaptation, limited market scale and energy efficiency, excessive feedback time costs, and low rate of economic return. To address these issues and ensure a secure energy market, we propose a decentralized intelligent V2G system called V2G Forecasting and Trading Network (V2GFTN) to achieve efficient and robust energy trading in campus EV networks. A multiple blockchain structure is proposed in V2GFTN to ensure trading security and data privacy between energy requests and offers. V2GFTN also integrates energy forecasting functions for EVs with a smart energy trading and EV allocation mechanism called SRET so that the EVs with driving tasks can supply their extra power back to the grid and achieve higher energy efficiency and economic profit. Through rigorous experimentation and compared with equivalent studies, V2GFTN system has demonstrated higher economic profit and energy demand fill rate by up to 1.6 times and 1.9 times than the state-of-the-art V2G approaches.