When Distributed Consensus Meets Wireless Connected Autonomous Systems: A Review and A DAG-based Approach

The connected and autonomous systems (CAS) and auto-driving era is coming into our life. To support CAS applications such as AI-driven decision-making and blockchain-based smart data management platform, data and message exchange/dissemination is a fundamental element. The distributed message broadcast and forward protocols in CAS, such as vehicular ad hoc networks (VANET), can suffer from significant message loss and uncertain transmission delay, and faulty nodes might disseminate fake messages to confuse the network. Therefore, the consensus mechanism is essential in CAS with distributed structure to guaranteed correct nodes agree on the same parameter and reach consistency. However, due to the wireless nature of CAS, traditional consensus cannot be directly deployed. This article reviews several existing consensus mechanisms, including average/maximum/minimum estimation consensus mechanisms that apply on quantity, Byzantine fault tolerance consensus for request, state machine replication (SMR) and blockchain, as well as their implementations in CAS. To deploy wireless-adapted consensus, we propose a Directed Acyclic Graph (DAG)-based message structure to build a non-equivocation data dissemination protocol for CAS, which has resilience against message loss and unpredictable forwarding latency. Finally, we enhance this protocol by developing a two-dimension DAG-based strategy to achieve partial order for blockchain and total order for the distributed service model SMR

Secure Harmonized Speed Under Byzantine Faults for Autonomous Vehicle Platoons Using Blockchain Technology

Autonomous Vehicle (AV) platooning holds the promise of safer and more efficient road transportation. By coordinating the movements of a group of vehicles, platooning offers benefits such as reduced energy consumption, lower emissions, and improved traffic flow. However, the realization of these advantages hinges on the ability of platooning vehicles to reach a consensus and maintain secure, cooperative behavior. Byzantine behavior [1,2], characterized by vehicles transmitting incorrect or conflicting information, threatens the integrity of platoon coordination. Vehicles within the platoon share vital data such as position, speed, and other relevant information to optimize their operation, ensuring safe and efficient driving. However, Byzantine behavior in AV platoons presents a critical challenge by disrupting coordinated operations. Consequently, the malicious transmission of conflicting information can lead to safety compromises, traffic disruptions, energy inefficiency, loss of trust, chain reactions of faults, and legal complexities [3,4]. In this light, this thesis delves into the challenges posed by Byzantine behavior within platoons and presents a robust solution using ConsenCar; a blockchain-based protocol for AV platoons which aims to address Byzantine faults in order to maintain reliable and secure platoon operations. Recognizing the complex obstacles presented by Byzantine faults in these critical real-time systems, this research exploits the potential of blockchain technology to establish Byzantine Fault Tolerance (BFT) through Vehicle-to-Vehicle (V2V) communications over a Vehicular Ad hoc NETwork (VANET). The operational procedure of ConsenCar involves several stages, including proposal validation, decision-making, and eliminating faulty vehicles. In instances such as speed harmonization, the decentralized network framework enables vehicles to exchange messages to ultimately agree on a harmonized speed that maximizes safety and efficiency. Notably, ConsenCar is designed to detect and isolate vehicles displaying Byzantine behavior, ensuring that their actions do not compromise the integrity of decision-making. Consequently, ConsenCar results in a robust assurance that all non-faulty vehicles converge on unanimous decisions. By testing ConsenCar on the speed harmonization operation, simulation results indicate that under the presence of Byzantine behavior, the protocol successfully detects and eliminates faulty vehicles, provided that more than two-thirds of the vehicles are non-faulty. This allows non-faulty vehicles to achieve secure harmonized speed and maintain safe platoon operations. As such, the protocol generalizes to secure other platooning operations, including splitting and merging, intersection negotiation, lane-changing, and others. The implications of this research are significant for the future of AV platooning, as it establishes BFT to enhance the safety, efficiency, and reliability of AV transportation, therefore paving the way for improved security and cooperative road ecosystems

Modeling a Consortium-based Distributed Ledger Network with Applications for Intelligent Transportation Infrastructure

Emerging distributed-ledger networks are changing the landscape for environments of low trust among participating entities. Implementing such technologies in transportation infrastructure communications and operations would enable, in a secure fashion, decentralized collaboration among entities who do not fully trust each other. This work models a transportation records and events data collection system enabled by a Hyperledger Fabric blockchain network and simulated using a transportation environment modeling tool. A distributed vehicle records management use case is shown with the capability to detect and prevent unauthorized vehicle odometer tampering. Another use case studied is that of vehicular data collected during the event of an accident. It relies on broadcast data collected from the Vehicle Ad-hoc Network (VANET) and submitted as witness reports from nearby vehicles or road-side units who observed the event taking place or detected misbehaving activity by vehicles involved in the accident. Mechanisms for the collection, validation, and corroboration of the reported data which may prove crucial for vehicle accident forensics are described and their implementation is discussed. A performance analysis of the network under various loads is conducted with results suggesting that tailored endorsement policies are an effective mechanism to improve overall network throughput for a given channel. The experimental testbed shows that Hyperledger Fabric and other distributed ledger technologies hold promise for the collection of transportation data and the collaboration of applications and services that consume it

Blockchain-Based Distributed Trust and Reputation Management Systems: A Survey

Distributed Ledger Technologies (DLTs), like Blockchain, are characterized by features such as transparency, traceability, and security by design. These features make the adoption of Blockchain attractive to enhance information security, privacy, and trustworthiness in very different contexts. This paper provides a comprehensive survey and aims at analyzing and assessing the use of Blockchain in the context of Distributed Trust and Reputation Management Systems (DTRMS). The analysis includes academic research as well as initiatives undertaken in the business domain. The paper defines two taxonomies for both Blockchain and DTRMS and applies a Formal Concept Analysis. Such an approach allowed us to identify the most recurrent and stable features in the current scientific landscape and several important implications among the two taxonomies. The results of the analysis have revealed significant trends and emerging practices in the current implementations that have been distilled into recommendations to guide Blockchain's adoption in DTRMS systems

Proof-of-Stake Consensus Mechanisms for Future Blockchain Networks: Fundamentals, Applications and Opportunities

© 2013 IEEE. The rapid development of blockchain technology and their numerous emerging applications has 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 the proof-of-work consensus mechanisms, in which the consensus is reached through intensive mining processes. However, this mechanism has several limitations, e.g., energy inefficiency, delay, and vulnerable to security threats. To overcome these problems, a new consensus mechanism has been developed recently, namely proof of stake, which enables to achieve the consensus via proving the stake ownership. This mechanism is expected to become a cutting-edge technology for future blockchain networks. This paper is dedicated to investigating proof-of-stake mechanisms, from fundamental knowledge to advanced proof-of-stake-based protocols along with performance analysis, e.g., energy consumption, delay, and security, as well as their promising applications, particularly in the field of Internet of Vehicles. The formation of stake pools and their effects on the network stake distribution are also analyzed and simulated. The results show that the ratio between the block reward and the total network stake has a significant impact on the decentralization of the network. Technical challenges and potential solutions are also discussed

Application of blockchain technology to 5G-enabled vehicular networks: survey and future directions

Blockchain is disrupting several sectors as it continues to grow mainstream. The attraction for Blockchain is increasing from various application domains looking to take advantage of its immutability, security, cost-saving, transparency and fast processing properties. Blockchain has empowered several sectors to upgrade their existing systems or operate an entire system architecture shift. For instance, Blockchain has enabled IoT systems to improve their quality of services while simultaneously ensuring their security requirements. Particularly, several works are applying Blockchain to manage trust in 5G-enabled autonomous vehicular systems to ensure secure vehicle authentication and handover, guarantee message integrity and provide an irrefutable vehicle reputation record. Vehicular network systems require proper data storage management, highly secure transactions, and non-interference networks. The immutability, tamper-proof, and security by design of Blockchain make it a suitable candidate technology for 5G vehicular network systems. We present in this paper a methodical literature analysis of the application of Blockchain to 5G vehicular networks, architecture, and technical aspects. We also highlight and discuss some issues and challenges facing the application of Blockchain technology to 5G vehicular network

APPLYING COLLABORATIVE ONLINE ACTIVE LEARNING IN VEHICULAR NETWORKS FOR FUTURE CONNECTED AND AUTONOMOUS VEHICLES

The main objective of this thesis is to provide a framework for, and proof of concept of, collaborative online active learning in vehicular networks. Another objective is to advance the state of the art in simulation-based evaluation and validation of connected intelligent vehicle applications. With advancements in machine learning and artificial intelligence, connected autonomous vehicles (CAVs) have begun to migrate from laboratory development and testing conditions to driving on public roads. Their deployment in our environmental landscape offers potential for decreases in road accidents and traffic congestion, as well as improved mobility in overcrowded cities. Although common driving scenarios can be relatively easily solved with classic perception, path planning, and motion control methods, the remaining unsolved scenarios are corner cases in which traditional methods fail. These unsolved cases are the keys to deploying CAVs safely on the road, but they require an enormous amount of data collection and high-quality human annotation, which are very cost-ineffective considering the ever-changing real-world scenarios and highly diverse road/weather conditions. Additionally, evaluating and testing applications for CAVs in real testbeds are extremely expensive, as obvious failures like crashes tend to be rare events and can hardly be captured through predefined test scenarios. Therefore, realistic simulation tools with the benefit of lower cost as well as generating reproducible experiment results are needed to complement the real testbeds in validating applications for CAVs. Therefore, in this thesis, we address the challenges therein and establish the fundamentals of the collaborative online active learning framework in vehicular network for future connected and autonomous vehicles.Ph.D

LVMM: The Localized Vehicular Multicast Middleware - a Framework for Ad Hoc Inter-Vehicles Multicast Communications

This thesis defines a novel semantic for multicast in vehicular ad hoc networks (VANETs) and it defines a middleware, the Localized Vehicular Multicast Middleware (LVMM) that enables minimum cost, source-based multicast communications in VANETs. The middleware provides support to find vehicles suitable to sustain multicast communications, to maintain multicast groups, and to execute a multicast routing protocol, the Vehicular Multicast Routing Protocol (VMRP), that delivers messages of multicast applications to all the recipients utilizing a loop-free, minimum cost path from each source to all the recipients. LVMM does not require a vehicle to know all other members: only knowledge of directly reachable nodes is required to perform the source-based routing

Coordination and Self-Adaptive Communication Primitives for Low-Power Wireless Networks

The Internet of Things (IoT) is a recent trend where objects are augmented with computing and communication capabilities, often via low-power wireless radios. The Internet of Things is an enabler for a connected and more sustainable modern society: smart grids are deployed to improve energy production and consumption, wireless monitoring systems allow smart factories to detect faults early and reduce waste, while connected vehicles coordinate on the road to ensure our safety and save fuel. Many recent IoT applications have stringent requirements for their wireless communication substrate: devices must cooperate and coordinate, must perform efficiently under varying and sometimes extreme environments, while strict deadlines must be met. Current distributed coordination algorithms have high overheads and are unfit to meet the requirements of today\u27s wireless applications, while current wireless protocols are often best-effort and lack the guarantees provided by well-studied coordination solutions. Further, many communication primitives available today lack the ability to adapt to dynamic environments, and are often tuned during their design phase to reach a target performance, rather than be continuously updated at runtime to adapt to reality.In this thesis, we study the problem of efficient and low-latency consensus in the context of low-power wireless networks, where communication is unreliable and nodes can fail, and we investigate the design of a self-adaptive wireless stack, where the communication substrate is able to adapt to changes to its environment. We propose three new communication primitives: Wireless Paxos brings fault-tolerant consensus to low-power wireless networking, STARC is a middleware for safe vehicular coordination at intersections, while Dimmer builds on reinforcement learning to provide adaptivity to low-power wireless networks. We evaluate in-depth each primitive on testbed deployments and we provide an open-source implementation to enable their use and improvement by the community