Commercialized 5G technology will provide reliable and efficient connectivity of motor vehicles that could support the dissemination of information under an intelligent transportation system. However, such service still suffers from risks or threats due to malicious content producers. The traditional public key infrastructure (PKI) cannot restrain such untrusted but legitimate publishers. Therefore, a trust-based service management mechanism is required to secure information dissemination. The issue of how to achieve a trust management model becomes a key problem in the situation. This paper proposes a novel prototype of the decentralized trust management system (DTMS) based on blockchain technologies. Compared with the conventional and centralized trust management system, DTMS adopts a decentralized consensus-based trust evaluation model and a blockchain-based trust storage system, which provide a transparent evaluation procedure and irreversible storage of trust credits. Moreover, the proposed trust model improves blockchain efficiency by only allowing trusted nodes participating in the validation and consensus process. Additionally, the designed system creatively applies a trusted execution environment (TEE) to secure the trust evaluation process together with an incentive model that is used to stimulate more participation and penalize malicious behaviours. Finally, to evaluate our new design prototype, both numerical analysis and practical experiments are implemented for performance evaluation.

This paper analyzes the performance of a short-packet non-orthogonal multiple access (NOMA) communication system assisted by an intelligent reflecting surface (IRS) whose reflecting elements suffer a certain failure probability. Both optimal phase shifts and one-bit phase errors are considered for the IRS. Closed-form asymptotic expressions for the average block error rate (BLER) at the NOMA users are obtained for both cases, which facilitate the investigation to the performance loss caused by phase errors and failure reflecting elements of the IRS. Numerical and simulation results have validated the accuracy of the developed theoretical analysis, and show that phase errors and partial failure reflecting elements of the IRS degrade the BLER performance of short-packet communications. They also show that IRS-aided short-packet NOMA systems outperform those in orthogonal multiple access in the whole signal-to-noise ratio range.

The advent of the Internet of Vehicles (IoV) has led to a significant surge in data generation from vehicles, prompting the innovative utilization of data transactions within the IoV environment. However, due to the inherent trustless nature of data transactions in IoV, concerns have arisen regarding the lack of trust between involved parties and the potential compromise of user privacy. To address these issues, blockchain technology emerges as a suitable decentralized distributed storage and security management solution, offering transparency and security in data transactions. In this study, we leverage blockchain to integrate with the IoV, devising a robust trust management framework, and devising a privacy protection scheme to safeguard user privacy concerns. Additionally, we employ the performance evaluation process algebra (PEPA) method for system modeling and performance analysis to assess the efficacy of our proposed solution. Empirical findings demonstrate that our approach effectively enhances the performance of data transactions within the IoV while ensuring that the privacy of users remains intact.

Formal method plays an important role in modeling large scale concurrent networks through its efficient model construction and analysis. Taking urban road networks and public transportation systems as examples, such models can be defined in a formal method in order to investigate the performance of current bus-line deployment based on a given road network. This paper considers how to efficiently build a formal model based on such an original prototype of the specified road network and transportation system. As the model prototype can be represented by a directed graph that is then transformed into a numerical incidence matrix, we proposed an algorithm, in this paper, to assist the construction of formal models by sorting all potential compositional structures and components based on the previously obtained numerical incidence matrix. Thereafter, a performance evaluation process algebra-based formal model can be automatically generated on the basis of sorted compositional structures, which extends the use of formal method for large-scale and comprehensive network, and system modeling. The findings reveal that the proposed algorithm can efficiently find all potential compositional structures that include all potential components and related activity flows in models.

Advanced communication technologies elicit a complete change of network and its applications. For example, a growing number of services begin shifting from central clouds to vast mobile devices, as the hybrid use of cloud and fog computing technologies can provide enhanced quality of service and efficient utilization of resources. However, to design such complex hybrid cloud-fog (HCF) systems, it remains a challenge to implement time-consuming modeling and inefficient evaluation in its early design stage based on the conventional simulation or practical experimentation. Therefore, how to reduce design cost and improve development efficiency becomes a crucial issue in the process of designing large-scale HCF systems. To address the issue, this paper proposes a novel modeling framework for large-scale HCF systems based on a high-level formal language, i.e. performance evaluation process algebra (PEPA). Toward the key components of an HCF system, the proposed framework includes three crucial model prototypes: compositional architecture model, abstract communication model and scheduling model. Moreover, the scheduling model is designed with a novel smart scheduling scheme that integrates two atomic scheduling algorithms and a decision module to make an efficient algorithm selection.The smart scheduling algorithm can well adapt the HCF systems by yielding stable and fast response.