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Register a new userReliable Traffic Monitoring Mechanisms Based on Blockchain in Vehicular Networks
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Added by
Jianxiong Guo
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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The real-time traffic monitoring is a fundamental mission in a smart city to understand traffic conditions and avoid dangerous incidents. In this paper, we propose a reliable and efficient traffic monitoring system that integrates blockchain and the Internet of vehicles technologies effectively. It can crowdsource its tasks of traffic information collection to vehicles that run on the road instead of installing cameras in every corner. First, we design a lightweight blockchain-based information trading framework to model the interactions between traffic administration and vehicles. It guarantees reliability, efficiency, and security during executing trading. Second, we define the utility functions for the entities in this system and come up with a budgeted auction mechanism that motivates vehicles to undertake the collection tasks actively. In our algorithm, it not only ensures that the total payment to the selected vehicles does not exceed a given budget, but also maintains the truthfulness of auction process that avoids some vehicles to offer unreal bids for getting greater utilities. Finally, we conduct a group of numerical simulations to evaluate the reliability of our trading framework and performance of our algorithms, whose results demonstrate their correctness and efficiency perfectly.
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With the increasing development of advanced communication technologies, vehicles are becoming smarter and more connected. Due to the tremendous growth of various vehicular applications, a huge amount of data is generated through advanced on-board devices and is deemed critical to improve driving safety and enhance vehicular services. However, cloud based models often fall short in applications where latency and mobility are critical. In order to fully realize the potential of vehicular networks, the challenges of efficient communication and computation need to be addressed. In this direction, vehicular fog computing (VFC) has emerged which extends the concept of fog computing to conventional vehicular networks. It is a geographically distributed paradigm that has the potential to conduct time-critical and data-intensive tasks by pushing intelligence (i.e. computing resources, storage, and application services) in the vicinity of end vehicles. However secure and reliable transmission are of significant importance in highly-mobile vehicular networks in order to ensure the optimal Quality of Service (QoS). In this direction, several authentication mechanisms have been proposed in the literature but most of them are found unfit due to absence of decentralization, anonymity, and trust characteristics. Thus, an effective cross-datacenter authentication and key-exchange scheme based on blockchain and elliptic curve cryptography (ECC) is proposed in this paper. Here, the distributed ledger of blockchain is used for maintaining the network information while the highly secure ECC is employed for mutual authentication between vehicles and road side units (RSUs). Additionally, the proposed scheme is lightweight and scalable for the considered VFC setup. The performance evaluation results against the existing state-of-the-art reveal that the proposed scheme accomplishes enhanced security features.
With the development of smart cities, not only are all corners of the city connected to each other, but also connected from city to city. They form a large distributed network together, which can facilitate the integration of distributed energy station (DES) and corresponding smart aggregators. Nevertheless, because of potential security and privacy protection arisen from trustless energies trading, how to make such energies trading goes smoothly is a tricky challenge. In this paper, we propose a blockchain-based multiple energies trading (B-MET) system for secure and efficient energies trading by executing a smart contract we design. Because energies trading requires the blockchain in B-MET system to have high throughput and low latency, we design a new byzantine-based consensus mechanism (BCM) based on nodes credit to improve efficiency for the consortium blockchain under the B-MET system. Then, we take combined heat and power (CHP) system as a typical example that provides distributed energies. We quantify their utilities, and model the interactions between aggregators and DESs in a smart city by a novel multi-leader multi-follower Stackelberg game. It is analyzed and solved by reaching Nash equilibrium between aggregators, which reflects the competition between aggregators to purchase energies from DESs. In the end, we conduct plenty of numerical simulations to evaluate and verify our proposed model and algorithms, which demonstrate their correctness and efficiency completely.
In this paper, we provide detailed analysis of the achievable throughput of infrastructure-based vehicular network with a finite traffic density under a cooperative communication strategy, which explores combined use of vehicle-to-infrastructure (V2I) communications, vehicle-to-vehicle (V2V) communications, mobility of vehicles and cooperations among vehicles and infrastructure to facilitate the data transmission. A closed form expression of the achievable throughput is obtained, which reveals the relationship between the achievable throughput and its major performance-impacting parameters such as distance between adjacent infrastructure points, radio ranges of infrastructure and vehicles, transmission rates of V2I and V2V communications and vehicular density. Numerical and simulation results show that the proposed cooperative communication strategy significantly increases the throughput of vehicular networks, compared with its non-cooperative counterpart, even when the traffic density is low. Our results shed insight on the optimum deployment of vehicular network infrastructure and optimum design of cooperative communication strategies in vehicular networks to maximize the throughput.
Recent advances in the integration of vehicular sensor network (VSN) technology, and crowd sensing leveraging pervasive sensors called onboard units (OBUs), like smartphones and radio frequency IDentifications to provide sensing services, have attracted increasing attention from both industry and academy. Nowadays, existing vehicular sensing applications lack good mechanisms to improve the maximum achievable throughput and minimizing service time of participating sensing OBUs in vehicular sensor networks. To fill these gaps, in this paper, first, we introduce real imperfect link states to the calculation of Markov chains. Second, we incorporate the result of different link states for multiple types of vehicles with the calculations of uplink throughput and service time. Third, in order to accurately calculate the service time of an OBU, we introduce the steady state probability to calculate the exact time of a duration for back-off decrement, rather than using the traditional relative probability. Additionally, to our best knowledge, we first explore a multichannel scheduling strategy of uplink data access in a single roadside unit (RSU) by using a non-cooperative game in a RSU coverage region to maximize the uplink throughput and minimize service time under saturated and unsaturated traffic loads. To this end, we conduct a theoretical analysis and find the equilibrium point of the scheduling. The numerical results show that the solution of the equilibrium points are consistent with optimization problems.
Crowd sensing is a new paradigm which leverages the pervasive smartphones to efficiently collect and upload sensing data, enabling numerous novel applications. To achieve good service quality for a crowd sensing application, incentive mechanisms are necessary for attracting more user participation. Most of existing mechanisms apply only for the budget-constraint scenario where the platform (the crowd sensing organizer) has a budget limit. On the contrary, we focus on a different scenario where the platform has a service limit. Based on the offline and online auction model, we consider a general problem: users submit their private profiles to the platform, and the platform aims at selecting a subset of users before a specified deadline for minimizing the total payment while a specific service can be completed. Specially, we design offline and online service-constraint incentive mechanisms for the case where the value function of selected users is monotone submodular. The mechanisms are individual rationality, task feasibility, computational efficiency, truthfulness, consumer sovereignty, constant frugality, and also performs well in practice. Finally, we use extensive simulations to demonstrate the theoretical properties of our mechanisms.
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