With the development of wireless communications, the 6G network is evolving toward dynamics, complexity, and integration. The mobility of nodes and intermittently of links lead to frequent variations in the network topology. When constructing the topology model, the reliability of topology is not only affected by the physical properties of wireless links but also related to the evolution process of nodes and links states, which is indispensable for improving the accuracy of the topology model. In this paper, we propose the evolution model based on dynamic bond percolation to characterize the reliable topology evolution. Firstly, key factors that cause the network topology changes are analyzed, integrating the characteristics of the node mobility and link channel conditions. Especially signal interference, buffer of nodes, and link availability are modeled for wireless link states. Then, the interactions between adjacent links are formulated by an extended Dynamic Bond Percolation (DBP) model to obtain the topology state transition matrix, which can accurately depict the change of link connection. Based on the quantitative analysis of wireless link states, Markov chain and master equation are employed to build the Dynamic Topology Evolution (DTE) model. Meanwhile, the network topology prediction problem is transformed into a linear system solution problem to obtain the steady-state network topology based on the DTE algorithm. Finally, the results suggest that utilizing the DTE model can significantly improve the accuracy of topology prediction and overall network performance.

In the study of information diffusion in social–physical networks, existing works are usually based on information entropy. These works measure and represent the information attribute characteristics independently for social networks and physical networks, resulting in ineffective interactions and waste of resources. Therefore, to solve the key problem of the mismatch between interaction demands and communication resources, the framework of collaborative diffusion based on value measurement is proposed in social–physical networks, including social–physical interaction, cognitive difference, and mutual trust degree of nodes. Based on parameterizing the relative strength of these influences by confidence and collaborative conservation factors, the collaborative diffusion model based on value measurement is established. Extensive simulations verify the influence of value measurement on the collaboration diffusion process, presented by the evolutions of value entropy, sentiment fragmentation, and diffusion range. In addition, the influence of collaboration on information dissemination is confirmed by the comparison of the change of value entropy and diffusion range. These results can help decision makers better balance the matching problem between interaction demands and available resources, which is beneficial to realize customized information diffusion.

The purpose of aspect-based sentiment analysis (ABSA) is to identify the sentiment polarity of a given aspect of a sentence. Recent investigations have revealed that incorporating syntactic structures derived from dependency-parsing trees into graph convolutional networks (GCNs) can yield excellent performance. However, these GCN-based methods excessively rely on the quality of the dependency-parsing tree, resulting possibly in suboptimal dependencies between words. Moreover, these GCN-based models fail to adapt properly to informal and complex comments without syntactic dependencies. To alleviate these deficiencies, we proposed a target-based GCN with semantic and syntactic information (TSGCN). In a TSGCN, a new target generation (NTG) module with a dependency attention mechanism is designed to generate a new target representation using explicit semantic information to replace a given aspect. Then, the syntactic structure is reconstructed based on the new target representation to capture the shortest distance between the given aspect and viewpoint words. Finally, the semantic structure generated by the self-attention mechanism was injected into the syntactic structure to complement the semantic dependencies between words. The experimental findings on five benchmark datasets indicated that the TSGCN outperformed the other baseline models .

Satellite formation flying with functional payloads can provide flexibility and real-time services for time sensitive missions through the cooperation of intra-satellite wired and inter-satellite wireless communication systems. However, the difference between wired and wireless scheduling mechanisms will increase the instability of forwarding delay at satellite. To solve this problem, we propose a wired and wireless converged scheduling scheme. Firstly, we construct the transmission rate and time division multiple access scheduling model to describe the inter-satellite link, and the IEEE 802.1Qbv scheduling model for wired link respectively. Secondly, we analyze the influence of the position of packet in different time slots on the forwarding delay, to model the relationship between the converged scheduling and forwarding delay. Finally, we formulate the converged scheduling as a zero-one programming problem with minimum jitter, and adopt the genetic-tabu search algorithm to solve it. Simulation results demonstrate that the delay is reduced by 20%, the jitter is not higher than$40\mu\mathrm{s}$.

As one of the essential paradigms of Industrial 4.0, the Industrial Internet of Things (IIoT) challenges existing data management and information services by supporting computational-intensive applications, in which devices share and receive information through interactions under resource constraints. When there exist diverse service requirements of IIoT applications, information dissemination will be more likely driven by service-oriented incentives. In this article, a novel information dissemination process with the service-oriented incentive mechanism is analyzed and modeled in IIoT, which depicts the dynamical evolution of IIoT devices’ interactions. In particular, the characteristics of service-oriented activating and dissemination degenerating are considered due to the unique capability of IIoT devices. Extensive theoretical and simulation results verify the dynamical behaviors of information dissemination, including the propagation threshold, equilibrium, and stability. In addition, comparative simulations have demonstrated the service-oriented incentive mechanism further expands information diffusion by driving the participation of IIoT devices.

The globalization process for integrated circuits (ICs) raises serious concerns regarding hardware Trojans (HTs). Due to the stealth and variety of HTs, detecting them at test time can be very resource intensive. This situation becomes even worse when the device under test (DUT) contains untrusted third-party intellectual property (3PIP) cores. For systems on chip (SoCs) that rely on untrusted 3PIP cores, this article solves the online HT detection and recovery problem from a graph-theoretic perspective. The proposed graph-theoretic models minimize the implementation cost of the system in terms of both the cost of purchasing different IP cores and the area overhead. To further enhance the security of the system, we also propose schemes to locate and replace an HT-infected IP core. The feasibility and efficiency of the proposed techniques are verified by experiments.

As the next‐generation power grid system, the smart grid can realize the balance of supply and demand and help in communication security and privacy protection. However, real‐time power consumption data collection might expose the users’ privacy information, such as their living habits and economic conditions. In addition, during the process of data transmission, it may lead to data inconsistency between the user side and the storage side. Blockchain provides tamper‐resistant and traceable characteristics for solving these problems, and ring signature schemes provide an anonymous authentication mechanism. Therefore, in this work, we consider the applications of ring signature scheme in smart grid based on blockchain. We introduce the notion of multi‐authority traceable ring signature (MA‐TRS) scheme for distributed setting. In our scheme, there is an auditing node that can distinguish the identity of the real signer from the ring without any secret information. Last but not least, we prove that the proposed scheme is unforgeable, anonymous, and traceable.