As the high-mobility nature of the vehicles results in frequent leaving and joining the transportation network, real-time data must be collected and shared in a timely manner. In such a transportation network, malicio...
详细信息
As the high-mobility nature of the vehicles results in frequent leaving and joining the transportation network, real-time data must be collected and shared in a timely manner. In such a transportation network, malicious vehicles can disrupt services and create serious issues, such as deadlocks and accidents. The blockchain is a technology that ensures traceability, consistency, and security in transportation networks. In this study, we integrated edge computing and blockchain technology to improve the optimal utilization of resources, especially in terms of computing, communication, security, and storage. We propose a novel, edge-integrated, blockchain-based vehicle platoon security scheme. For the vehicle platoon, we developed the security architecture, implemented smart contracts for practical network scenarios in network simulator version 3, and integrated them with the simulation urban mobility traffic control interface API. We exhaustively simulated all the scenarios and analyzed the communication performance metrics, such as throughput, delay, and jitter, and the security performance metrics, such as mean squared error, communication, and computational cost. The performance results demonstrate that the developed scheme can solve security-related issues more effectively and efficiently in smart cities.
Device-to-device (D2D) communication, which enables information transmission without relying on base stations (BS), has become one of the key technologies in 5G/6G networks. In communication, D2D users share channels ...
详细信息
ISBN:
(纸本)9798350361261;9798350361278
Device-to-device (D2D) communication, which enables information transmission without relying on base stations (BS), has become one of the key technologies in 5G/6G networks. In communication, D2D users share channels with cellular users, and managing interference among multiple users becomes a complex task. Existing deep learning-based schemes suffer from the following issues: the channel state information (CSI) of the system is treated as independent features, neglecting the topological relationship between users and channels;compared to half-duplex, full-duplex resource allocation schemes are fewer and more complex. Therefore, this paper explores and proposes several full-duplex D2D communication resource allocation models based on graph neural network (GNN). One approach is to design a GNN model based on cumulative channel gains, which merges multiple channel graph structures into one and performs information propagation and exchange on the graph. Another approach is to independently execute GNN modeling on each channel graph structure, and use attention mechanism or Concat method at the output end for fusion. In distributed resource allocation architecture, the GNN model is used to construct and compute information received from users at the BS. In terms of networkarchitecture, graph convolutional network and graph attention network are alternately fused to leverage their strengths and improve the stability of the model. all the proposed models have been validated under different scenarios and parameters, demonstrating superior overall performance compared to a traditional heuristic algorithm and several recent DNN models.
With the continuous deepening of the application of 5G technology in various industries, the aviation industry's flight test business is also accelerating the rapid transformation and upgrading of the 5G aviation ...
详细信息
With the advancements in IoT technology, cloud computing, and big data technology, smart living has become an integral part of people's lives. However, traditional intelligent data computing relies heavily on clou...
详细信息
Monolithic architecturesystems encapsulate all functions in a single deployment unit. With the complexity of business requirements increasing, monolithic architecturesystems require significant human resources to ma...
详细信息
The efficiency and performance of neural network (NN) controllers present a significant challenge in the rapidly evolving landscape of real-time closed-loop controlsystems, such as those used in solar inverters. This...
详细信息
ISBN:
(纸本)9798331540913;9798331540906
The efficiency and performance of neural network (NN) controllers present a significant challenge in the rapidly evolving landscape of real-time closed-loop controlsystems, such as those used in solar inverters. This paper introduces a novel approach that enhances training efficiency by combining adaptive dropout with parallel computing techniques, utilizing the Levenberg-Marquardt (LM) algorithm and Forward Accumulation Through Time (FATT). Unlike traditional dropout methods that apply a fixed dropout rate uniformly across all neurons, Adaptive Dropout dynamically adjusts the dropout rate based on each neuron's calculated importance and its stage in the training process. This allows for the protection of more critical neurons while regularizing less significant ones, thereby improving convergence speed and enhancing generalization in the neural networkcontroller. To further accelerate the training process, the Adaptive Dropout method is seamlessly integrated into a parallel computing architecture. This architecture employs multiple cores to compute Dynamic Programming (DP) costs and Jacobian matrices for various trajectories simultaneously. This approach not only harnesses the computational power of modern multi-core systems but also ensures efficient processing across all trajectories. The experimental results demonstrate that adaptive dropout with parallel computing provides improvements in training efficiency and overall performance than both no dropout and weight dropout control schemes.
As cloud-network integration, 5G and 6G, all-opticalnetwork, and IP-based services evolve, operational systems of operators face new challenges. The current operational systems suffer from inconsistent technical arch...
详细信息
The high proportion of new energy sources integration causes issues such as load imbalance and high complexity in resource management. Low resource utilization has emerged in the power communicationnetwork. It is urg...
详细信息
With the widespread application of 5G networks, next-generation mobile communicationsystems are actively being studied. In order to solve the problem of difficult coverage of high-frequency signals, researchers have ...
详细信息
Coherent detection has emerged as a key technology for advancing passive opticalnetworks (PON) beyond 100 Gbps per wavelength, due to its advantages over the intensity and direct-detection (IM/DD) approach, which was...
详细信息
暂无评论