Multi-Channel Blockchain Scheme for Internet of Vehicles

Abstract

With the development of advanced information and communication technology, the traditional centralized service model alone no longer meets the increasing demand of data exchange in intelligent transportation systems (ITS). While Internet of Vehicles (IoV) technology has been introduced to achieve more advanced ITS, there are still some unsettled issues such as flexibility and fault tolerance. The conventional centralized approach for ITS is vulnerable to the single point of failure, and lack of flexibility due to its dependence on a trusted third party (TTP). The emergence of blockchain technology provides a potential direction to address these problems. However, due to varying vehicle densities, it is challenging to select the best blockchain parameters to satisfy the application requirements. In this paper, we propose a multi-channel blockchain scheme that can use the best parameters in accordance with the vehicle density. The proposed scheme first defines multiple blockchain channels where each channel is optimized for a certain vehicle density level. Then, the system selects the best channel according to the vehicle density, and the application requirements on the transaction throughput and latency. We use extensive simulations to show that the proposed blockchain scheme achieves a significantly better performance as compared with existing baselines.INDEX TERMS Blockchain, IoV, hyperledger fabric, channel management.

A quality of service‐aware high‐security architecture design for software‐defined network powered vehicular ad‐hoc networks using machine learning‐based blockchain routing

“…Similarly, the energy consumption of these protocols can be observed from Table 5 as follows, where the average value of energy at Reference 4 is 14.4 mJ, Reference 8 is 17.18 mJ, Reference 33 is 12.63 mJ and at QHS‐SDN‐VANET‐MLB is 9.68 mJ. The energy consumption has been reduced by 33% when compared with Reference 4, 38.8% with Reference 8, and 19.95% with Reference 33; this is due to the optimization of energy in the fitness function during routing.…”

“…To remove this drawback, the works in References 33,34 propose the use of ML and AI models with stacked autoencoders and network virtualization. These ML and AI models assist in finding optimum solutions for the given blockchain, and thereby tune its performance as network size increases.…”

HeteroFL Blockchain Approach-Based Security for Cognitive Internet of Things

“…e proposed method improves the latency, transaction success ratio, and through put for varying number of vehicles [12]. e decentralized model for huge data based on cognitive processing, federated learning, and blockchain together is fostered.…”

Strategies for Improving the Sustainability of Data Centers via Energy Mix, Energy Conservation, and Circular Energy

“…The first application of blockchains has been to support bitcoin transactions; today, they are regarded as disruptive in many applications [20,21], including climate change [22], energy [23], and health [24]. A recent application of blockchains is in smart mobility, supporting Internet-of-Vehicles [25]. The energy and environmental impact of blockchains is investigated [17,26].…”