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Nowadays, a large number of intelligent devices involved in the Industrial Internet of Things (IIoT) environment are posing unprecedented cybersecurity challenges. Due to the limited budget for security protection, the IIoT devices are vulnerable and easily compromised to launch Distributed Denial-of-Service (DDoS) attacks, resulting in disastrous results. Unfortunately, considering the particularity of the IIoT environment, most of the defense solutions in traditional networks cannot be directly applied to IIoT with acceptable security performance. Therefore, in this work, we propose a multi-point collaborative defense mechanism against DDoS attacks for IIoT. Specifically, for the single point DDoS defense, we design an edge-centric mechanism termed EdgeDefense for the detection, identification, classification, and mitigation of DDoS attacks and the generation of defense information. For the practical multi-point scenario, we propose a collaborative defense model against DDoS attacks to securely share the defense information across the network through the blockchain. Besides, a fast defense information sharing mechanism is designed to reduce the delay of defense information sharing and provide a responsive cybersecurity guarantee. The simulation results indicate that the identification and classification performance of the two machine learning models designed for EdgeDefense are better than those of the state-of-the-art baseline models, and therefore EdgeDefense can defend against DDoS attacks effectively. The results also verify that the proposed fast sharing mechanism can reduce the propagation delay of the defense information blocks effectively, thereby improving the responsiveness of the multi-point collaborative DDoS defense.

The rapid development of mobile multimedia services integrated with online and offline social networks has made the mutual transmission of smart devices more frequent. Device to Device relay communication (D2D relay communication) can extend the transmission range of shared multimedia services, further reducing the burden on the base stations. However, when multimedia services are transmitted by D2D relay communication, the selfishness of the relay nodes affects the quality of the transmission. In order to solve this problem, the integration of social factors has become a common research topic. However, social factors generally come from multi-dimensional information. The more kinds of information, the more hidden information, and the measurement of social relations will become extremely difficult. Hence, this paper focuses on the measurement of social relationships based on multi-dimensional information and then combines physical domains to choose relay nodes. Firstly, the transmission performance of D2D relay communication is analyzed in the physical domain. Then, in order to better integrate multi-dimensional information, we construct a hypernet architecture based on spatiotemporal-user-location-category and quantify the edge weights. Three categories of weighted super-edge structures are defined to capture a variety of hidden social relationships, and the social relationship strength of any two users is measured. Finally, a relay selection algorithm that maximizes the social rate is proposed, which combines social relationships of multi-dimensional information and quality of physical transmission. The simulation results show that the Based on Maximum Social Rate for Relay Selection Algorithm (MSRRS) proposed in this paper has a significant improvement in transmission quality and transmission stability for multimedia application compared with the traditional relay selection algorithm.

Recently, the rapid development of mobile multimedia intelligent voice systems has affected the rapid changes in user interaction. Meanwhile, the continuous optimization of recommended algorithms makes the change of interaction mode from the original user's active search to the machine actively recommending continuously. It is an inevitable trend that multimedia intelligent voice dialogue system brings more efficient content services to users through active recommendation. However, the existing multimedia intelligent voice dialogue systems are mainly based on the user's expression content to analyze the user's subject willingness and then provide the reply contents to user. This kind of interaction only drives the topic through the user, which will cause some problems like single chat topic and missing points of interest. In order to address these problems, this paper proposes an interactive topic guiding model. This model uses the surrounding similar users and user context information to guide users' topics, and taking into account the harmony of human-computer interaction, the game method is adopted to select the optimal content response strategy by considering the user's and robot's emotional friendliness and content friendliness. The experiments show that the model proposed in this paper can effectively guide topics. Moreover, it has significant improvement in content richness compared with other models in human-machine natural interaction, which can provide some research ideas for guiding the topic in the mobile multimedia intelligent voice system.

Along with the advances of virtual reality (VR) technologies, VR applications are found in various fields. For example, at many major exhibitions, VR is used to mimic the real world through utilizing a number of on-spot sensory equipment to provide immersive user experiences. Despite the advantages that VR brings, the enormous amount of distributed VR videos and the high density of VR users may impose a heavy burden on base stations. On the other hand, the quality of experience (QoE) may seriously suffer from the transmission delay and monetary costs of VR videos. To address the above issues, a D2D-assisted VR video distribution system is designed, and a pre-caching algorithm based on QoE gain is proposed. More specifically, by observing the user residence time at a given node, a user can pre-cache VR videos at the nodes to be visited for improved QoE. To achieve better veracity and efficiency of the pre-caching algorithm, the probability of a user entering each node is calculated based on that user's interest and nodes' popularity. Furthermore, the set of candidate schemes can be greatly narrowed down to a range of feasible schemes according to the real-time popularity threshold, the available storage space, and the energy of the user's equipment. The scheme with maximized user's QoE can finally be selected from the candidate sets according to user's QoE gain. Numerical results show that our proposed pre-caching algorithm improves the level of user's QoE while maintaining superior stability compared with the random-caching and greedy-caching algorithms.

In order to improve the communication quality of relay-based D2D communication, this paper proposed a relay selection algorithm with the consideration of the information of the social domain and the physical domain. First, the transmission performance of D2D relay communication in the half-duplex relay mode and the full-duplex relay mode is analyzed separately in the physical domain. Second, we analyzed the user’s history check-in information to obtain the characteristics of user’s mobility and the social relationship strength between users. Finally, we proposed a relay communication gain metric to measure the extent of transmission performance improvement brought by D2D relay communication and developed a relay selection algorithm for maximizing the relay communication gain. The simulation results show that compared with the traditional D2D relay communication scheme, the transmission rate and stability of the transmission link of the D2D relay communication system using the proposed algorithm are greatly improved.

Relay-assisted Device-to-Device (D2D) communication, one of the important transmission modes in mobile health systems, can provide high transmission quality for servicing users at the edge of system coverage. However, the quality of the D2D relay communication is largely limited by the relay nodes. When a poor node is selected to assist the source node in the data transmission, it is likely to result in the loss of medical data and inaccurate transmission. Therefore, this paper focuses on how to select relay modes and relay nodes to improve the reliability of medical data transmission. Firstly, in order to eliminate the relay nodes with low energy or poor willingness, the acceptable energy consumption metric of relay nodes is proposed in this paper. The relay mode of each relay node is determined by the acceptable energy consumption metric, which can ensure the physical reliability of the relay communication links. Then a trust metric is proposed to measure the social reliability of each relay link, further excluding the malicious relay nodes. Finally, this paper proposes a relay selection algorithm based on compromise factors (RSCF). With the help of the proposed algorithm, the reliability of the relay communication can be guaranteed, and the spectrum efficiency can be promoted greatly. The simulation results show that the relay nodes selected by RSCF algorithm can greatly improve transmission rate and reliability compared with the traditional relay-assisted D2D communication schemes.

There are a large number of redundant transmissions in current D2D multicast content delivery systems, which seriously reduces the utilization efficiency of resources. This paper designs a novel user-information-aware D2D video distribution mechanism. More specifically, by predicting users’ video requests, the video can be pushed to potential service requesters while distributing video for service requesters. Firstly, the willingness of potential requesters to accept the pushed video is estimated based on the users’ interests, the popularity of the videos and the residual-energy of the users’ devices, and the user-demand-aware clustering algorithm is proposed. Secondly, considering social and interference information, the utility metric of D2D multicast is proposed to measure the value of content distribution service. Finally, this paper proposes a D2D video distribution mechanism to optimize the utility value. Simulation results show that the proposed mechanism significantly improves throughput, energy and spectrum efficiency compared to the traditional distribution mechanism.

We consider the nonlinear propagation of an optical beam in a two-dimensional waveguide matrix, which is described by the discrete nonlinear Schrödinger equation with a self-focusing nonlinearity. Our study focuses on the stability domain of the discrete vortex solitons with its topological invariant S equal to 1. Such domain is identified with the propagation constant k and the coupling constant C. Our simulations show that there is a critical value Ccr for any fixed value of k. At C ≤ Ccr, the stable domain is continuous. However, at C > Ccr, the stable domain becomes discontinuous and fuzzy. The distribution of the continuous stable regions is identified and plotted. Moreover, we give the relation of the total power P to C and k, which enable us to figure out the continuous stability area through the (P, C) plane. [ABSTRACT FROM AUTHOR]