Junhua Wu

A large-scale Internet of Things (IoT) system based on sharded blockchain technology faces challenges, such as excessively high Cross-Shard Transaction (CST) ratios and imbalanced internal consensus. Current solutions include designing sharding protocols and consensus algorithms. However, these previous approaches solely focus on the outcomes of sharding, neglecting the intricate consensus costs incurred during the sharding process. This seriously affects the transaction latency of the system. Therefore, in this paper, we propose a latency optimization scheme. This scheme includes the sharding algorithm based on Weighting in K-means (W-K-means) clustering (namely WK-shard) and the Best Stable Committee (BSC) algorithm, aimed at addressing challenges in committee formation latency and internal consensus latency during the sharding process. Specifically, the WK-shard algorithm utilizes W-K-means clustering to balance the relationship between CSTs and intra-shard computility allocation. This ensures load balancing across shards while reducing CSTs, providing a strong basis for user nodes to select appropriate shards. Meanwhile, the BSC algorithm utilizes Markov chains to solve for the steady-state committee. The optimal utility of problem is explored through the dynamic state transitions of the schemes selected by different committees. A good selection scheme can reduce the total interval time of the system, effectively resolve the problem of laggards in internal consensus. We analyze the transaction lantency and validity degree of the latency optimization scheme through experiments, and compare it with other algorithms. The experimental results show that the proposed WK-shard algorithm reduces the committee formation latency by 15%, and the average validity degree of the BSC algorithm increases by 0.4 Transaction Per Second (TPS).

The integration of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) mounted on unmanned aerial vehicles (UAVs) offers a promising approach to enhancing wireless coverage and connectivity. However, practical deployment faces significant challenges due to STAR-RIS misalignment caused by UAV-induced vibrations and orientation offsets of the STAR-RIS substrate. To address these issues, this paper proposes a UAV-enabled aerial STAR-RIS multiple-input single-output (MISO) communication network that explicitly accounts for vibration-induced offsets and the orientation deployment of a vertically mounted STAR-RIS. By incorporating vibration offset compensation and orientation deployment strategies, a unified optimization framework is proposed to jointly optimize the UAV flight trajectory and STAR-RIS beamforming, thereby maximizing the system sum data rate. To handle the high-dimensional complexity and long-term exploration challenges inherent in dynamic optimization problems, a deep reinforcement learning (DRL) approach based on robust policy optimization (RPO) is adopted. This method introduces uniform perturbations into the action distribution to enhance policy entropy and exploration, improving training stability and overall performance. Extensive simulation results demonstrate that the proposed co-design framework significantly outperforms the conventional proximal policy optimization (PPO) algorithm, achieving faster convergence. Moreover, the orientation deployment of the UAV-mounted STAR-RIS yields a substantial improvement in the sum data rate. Even under high signal-to-noise ratio (SNR) conditions, the joint optimization of orientation control and vibration offsets closely approaches the ideal benchmark.

The application of blockchain technology to the field of e-commerce has solved many dilemmas, such as low transparency of transactions, hidden risks of data security and high payment costs. Mobile edge computing(MEC) can provide computational power for blockchain, and can meet the demand for high real-time and low latency in e-commerce transaction systems. However, there are still some constraints in the MEC enabled e-commerce consortium blockchain, such as the leakage of user privacy information, low security of consensus algorithm and other security issues. In this paper, we propose a secure transaction model suitable for MEC enabled e-commerce consortium blockchain, aiming to ensure the efficiency of system transaction processing while improving the security of users’ privacy information and transaction data. The model adopts the lightweight Paillier encryption algorithm to protect the security of user privacy information and transaction data to prevent the leakage of user privacy information, and optimizes the security of leader election phase of Raft consensus algorithm by introducing the shamir secret sharing protocol to improve the anti-Byzantine failure capabilities of Raft consensus algorithm. The effectiveness of the scheme proposed in this paper is demonstrated by experimental simulations.

The application of blockchain technology to the field of e-commerce has solved many dilemmas, such as low transparency of transactions, hidden risks of data security and high payment costs. However, there are still constraints in the existing e-commerce consortium blockchain, such as the leakage of users' privacy information, the incomplete traditional consensus algorithm, and the severely insufficient blockchain performance. In this paper, we propose a secure and efficient transaction model applicable to e-commerce consortium blockchain, aiming at guaranteeing the security of user privacy information and transaction data while improving the transaction processing efficiency of the system. The model uses homomorphic encryption algorithm to maintain the confidentiality of user transaction information, and improves the Byzantine resistance of the Raft consensus algorithm while retaining its simplicity and efficiency. The effectiveness of the scheme proposed in this paper is demonstrated by experimental simulations.

More and more people choose to use electric vehicles to protect the environment and conform to the trend of sustainable development. However, the increase in the number of electric vehicles may cause problems with the overload of the grid, and electric vehicles have their shortcomings of weak range. Vehicle-to-vehicle energy trading can balance the load on the grid and alleviate the range anxiety of electric vehicles. Existing studies focus more on transaction efficiency and energy utilization, ignoring data security and user privacy during the transaction process. To this end, this paper proposes a blockchain-based V2V energy security transaction scheme, which records the data of the transaction process on the blockchain, and realizes the registration, authentication, and transaction process through smart contracts. Furthermore, we propose a transaction matching scheme, which fully accounts for both parties' credibility and uses the Bayesian game to determine the transaction price. Under the premise of an incomplete exchange of information, both parties shall ensure the reliability of the transaction and obtain the optimal price. Finally, the algorithm performance is evaluated through simulation, which shows that the scheme is close to the bidding price of both parties, and the high user satisfaction ensures a higher matching success rate for both parties. Considering the trust value matching and pricing scheme can be a good way to limit the behavior of both sides of the transaction, and ensure the credibility of both sides and the security of the transaction.

Achieving efficient and secure sharing of data in the Internet of Vehicles (IoV) is of great significance for the development of smart transportation. Although blockchain technology has great potential to promote data sharing and privacy protection in the context of IoV, the problem of securing data sharing should be payed more attentions. This paper proposes an IoV data sharing scheme based on the hybrid architecture of blockchain and cloud-edge computing. Firstly, to improve protocol’s efficiency, a dual-chain structure empowered by alliance chain is introduced as the model architecture. Secondly, for the space problem characterized by data storage and security, we adopt distributed storage with the help of edge devices. Finally, to both ensure the efficiency of consensus protocol and protect the privacy of vehicles and owners simultaneously, we improve DPoS consensus algorithm to realize the efficient operation of the IoV data sharing model, which is closer to the actual needs of IoV. The comparison with other data sharing models highlights the advantages of this model, in terms of data storage and sharing security. It can be seen that the improved DPoS has high consensus efficiency and security in IoV.