With the development of the energy Internet, power communication services are heterogeneous, and different power communication services have different business priorities. The power communication services with different priorities have different requirements for network bandwidth and real-time performance. For traditional unified service, a scheduling method cannot meet these service requirements at the same time, and electric power communication network cannot guarantee the quality of service. Therefore, how to make full use of the time-varying characteristics of communication resources to meet the business needs of different priorities and achieve the goals of high resource utilization and transmission quality has become one of the urgent problems in the power communication network. For this reason, in order to adapt to the real-time congestion of the network, we have designed a packet scheduling method based on the dynamic adjustment of service priority, which dynamically adjusts the priority of the power service on the node; in addition, an evaluation method for the trust value of wireless forwarding nodes is introduced to improve the security of data transmission; and finally, we valuate the channel quality to establish a reasonable and efficient packet scheduling mechanism for services of different priorities. Simulation results show that this method improves the communication performance of high-priority services and improves the spectrum resource utilization of the entire system.
Bandwidth Prediction for Business Requirement of Electric Power Communication Network with Deep-Learning
