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This paper analyzes the network architecture of the Iridium system, Orbcomm system, Narrow Band-Internet of Things (NB-IoT) and Long Range Radio (Lo Ra) in the satellite 5G mobile communication system. A new Dynamic Routing based on Multi-factor Forwarding (MF-DR) protocol is proposed. This paper simulates the ladder-type data fusion algorithm in terms of energy consumption in the Wireless Sensor Network (WSN), the number of surviving nodes in the WSN, the communication traffic in the WSN, and the applicability of the ladder-type fusion algorithm. This verifies the superiority of the improved data fusion algorithm. [ABSTRACT FROM AUTHOR]

Energy-efficient is a challenging issue in Wireless Sensor Network, which is a promising technology being widely used in the planetary exploration. Considering the rechargeable solar batteries equipped in the planetary surface sensor system, this paper presents a novel and special dual-mode energy-driven (DMED) routing protocol for the planetary exploration. According to the charging and sleeping states of the solar battery, the dual modes (i.e. day mode and night mode) of the node are obtained. Differential theory is adopted in the DMED weighted average of reciprocals consultation mechanism to choose the optimal value of $$p$$ which can be adjusted dynamically under dual modes. The experimental results indicate that DMED is superior to ad hoc on-demand distance vector in the performance of energy balancing, and it prolongs the network lifetime effectively. The research of this work is benefit to the planetary exploration, and the research results provide reference value to the special routing protocol design. [ABSTRACT FROM AUTHOR]

In this paper, we propose a secure and efficient trust scheme with Bayesian theory to detect whether a node is malicious or not. In order to improve the correctness of detecting behavior, we aim to consider the influence with respect to the internal attacks of compromised nodes as many as possible. Moreover, the information of malicious behaviors is collected by their neighboring nodes and fused by the foregoing hop nodes. And then, the trust value concerning some node is computed by its father node in a route. Moreover, the key exchange of a secure route is implemented by the modified Diffie-Hellman key agreement protocol to guard against man-in-the-middle attack. The simulation results show that, with the increase of trust ratio, the Bayesian theorem can make more credible judgment on whether the network nodes are secure than the Beta function and the efficient clustering scheme for group key management in the present of malicious nodes. [ABSTRACT FROM AUTHOR]

The progress of science and technology and the expansion of the Internet of Things make the information transmission between communication infrastructure and wireless sensors become more and more convenient. For the power-limited wireless sensors, the life time can be extended through the energy-harvesting technique. Additionally, wireless sensors can use the unauthored spectrum resource to complete certain information transmission tasks based on cognitive radio. Harvesting enough energy from the environments, the wireless sensors, works as the second users (SUs) can lease spectrum resource from the primary user (PU) to finish their task and bring additional transmission cost to themselves. To minimize the overall cost of SUs and to maximize the spectrum profit of the PU during the information transmission period, we formulated a differential game model to solve the resource allocation problem in the cognitive radio wireless sensor networks with energy harvesting, considering the SUs as the game players. By solving the proposed resource allocation game model, we found the open loop Nash equilibrium solutions and feedback Nash equilibrium solutions for all SUs as the optimal control strategies. Ultimately, series numerical simulation experiments have been made to demonstrate the rationality and effectiveness of the game model. [ABSTRACT FROM AUTHOR]

Most of the wireless nodes in the Internet of Things (IoT) environment face the limited energy problem and the way to provide a sustainable energy for these nodes has become an urgent challenge. In this paper, we present an unmanned aerial vehicle (UAV) to power the wireless nodes in the IoT and an investigation on the optimal resource allocation approach based on dynamic game theory. This IoT system consists of one UAV as the power source and information receiver. The wireless nodes can be powered and collected by the UAV. In order to distinguish the wireless nodes, the wireless nodes are divided into two categories based on the energy consumption. The UAV tries to power these two categories of nodes using a different power level based on the proposed approach, where the wireless nodes control the resources for information transmission. Based on Bellman dynamic programming, the optimal allocated resources for power transfer and information transmission are obtained for both the UAV and wireless nodes, respectively. In order to show the effectiveness of the proposed model and approach, we present numerical simulations. [ABSTRACT FROM AUTHOR]