With the advancement of technology, China is developing rapidly in the construction of emergency communication systems. Currently, emergency communication networks have an urgent demand for multimedia services and higher requirements for network bandwidth. When there are multiple different services in the network, traditional universal routing protocols are no longer applicable and cannot simultaneously meet the transmission requirements of different business flows. There is a common problem with the existing encoding aware routing in the power emergency communication MESH network. In order to improve network performance, a large amount of data flow is concentrated on certain nodes to create more encoding opportunities. When the data flow increases to a certain extent, these nodes will cause local congestion or even paralysis due to heavy load. A new routing metric has been proposed, and based on this metric, a coding aware load balancing routing strategy has been proposed. This routing strategy not only utilizes network coding to save network resources and improve network throughput, but also considers the load situation of nodes. It selects nodes with relatively light load as the next hop node to forward, achieving a balance between network coding and node load balancing. The simulation results show that in scenarios with different data transmission rates, this routing strategy can effectively alleviate network congestion, with higher network throughput and lower end-to-end latency.
KEYWORDS: Power grids, Particles, Particle swarm optimization, Monte Carlo methods, Computer simulations, Reliability, Data communications, Wireless communications, Spatial learning, Multiplexing
In order to effectively improve the efficiency and reliability of power grid communication and promote the intelligent development of the power grid, a multi agent 5G communication terminal resource allocation method considering randomness has been proposed for the power grid. Considering the randomness factor, the Monte Carlo method is used to complete the random power flow calculation of the multi-agent 5G communication terminal of the power grid. On this basis, a multi-agent 5G communication terminal resource allocation model for the power grid is constructed, and a hybrid particle swarm optimization algorithm is used to solve the multi-agent 5G communication terminal resource allocation model for the power grid, achieving multi-agent 5G communication terminal resource allocation. The experimental results show that the proposed method has good resource allocation performance for multi-agent 5G communication terminals in the power grid, and can effectively improve resource allocation efficiency.
KEYWORDS: Data transmission, Data compression, Receivers, Data communications, Optical transmission, Optical fibers, Power grids, Fiber optic communications, Reliability, Network architectures
The differential protection of distribution network has good selectivity and quick action, but it is difficult to apply in areas where the laying rate of optical fiber is not high. The emergence of 5G communication technology with low delay and high reliability provides a new communication solution for the application of distribution network differential protection technology. However, the 5G distribution network differential protection has a large amount of differential current data in its application, which leads to the problem of large data flow and high cost of 5G communication terminals. This paper proposes a scheme of adding differential protection data compression transmission technology to the 5G terminal, which not only does not affect the differential protection service, but also saves the communication data flow, providing a reference for the wide application of 5G technology in differential protection in the future.
In the Internet of Things (IoT) environment, embedded IoT devices have limited computing and storage resources. Their data lacks encryption protection. To solve this problem, this paper proposes a lightweight encryption algorithm based on SM4. First, this paper analyzed the encryption and decryption principle of SM4 algorithm. Then the S-box used in the encryption and decryption process was extended from high-order domain to low-order domain. The S-box component is constructed by a few logic gates to realize the lightness of the algorithm. Finally, the optimized SM4 module was embedded in the 5G communication terminal for testing. The results show that the lightweight encryption algorithm for IoT device can adapt to the data encryption of resource-constrained devices well. It is helpful to avoid the data leakage.
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