Research On Low-latency Communication Routing Techniques For Power Internet Of Things

The traditional power grid data transmission mainly uses optical fiber as the transmission medium.However,with the increase in the number of power grid terminals and the increasing demand for power supply reliability by users,the traditional power grid has problems such as poor transmission performance,high construction costs,and difficulty in later reconstruction.As one of the important vertical industries of 5G,the power Internet of Things combines the new generation of communication technology with the traditional power transmission system.The flexible configuration of the power grid can build a service-oriented dedicated transmission network,improve the transmission performance of power grid data,and reduce the operation and maintenance costs of the power grid.However,the power Internet of Things with 5G as the communication mode has new problems such as large transmission delay jitter and low resource utilization rate.Against this background,this thesis studies the low-latency communication routing techniques for the Power Internet of Things.The main contributions of this thesis are listed as follows:Firstly,the data transmission model of the power Internet of Things scenario is considered,in which the data of the sending terminal is forwarded by several routing nodes to the receiving terminal under the scheduling of the SDN controller.A network slicing and routing method of power Internet of Things business is proposed.The grid data transmission delay is the optimization goal.Under the condition of limited transmission bandwidth resources,the SDN controller takes the transmission delay between routing nodes as weight,allocates the underlying bandwidth resources on-demand,selects the optimal routing transmission path,reduces the end-to-end transmission time of the sender and the receiver,and improves the transmission efficiency of the network.The simulation results show that the proposed routing optimization method has a lower system transmission delay compared with the random routing method.Secondly,the end-to-end communication model for delay-sensitive services and high-speed transmission services in the power Internet of Things is considered.The two types of service data are sent from the sending terminal and reach the receiving terminal through the transmission of the access network and the core network.A low-latency routing transmission method based on the joint optimization of the access network and core network bandwidth is proposed.Taking the total transmission delay of delay-sensitive services of the power Internet of Things scenario as the optimization goal,and in the case of meeting the service quality requirements of high-speed transmission services,a nonlinear planning is used to joint optimize access network and core network bandwidth resource of delay-sensitive services,allocate transmission bandwidth between wireless access network and core network,and optimize service routing resources.The simulation results show that the proposed routing transmission method is superior to the bandwidth-sharing scheme in terms of transmission delay.Finally,a data transmission model of the core network in the power Internet of Things is considered,transmission data packets are forwarded from the sender to the receiver through each routing node according to the path arrangement of the SDN controller.A multi-path low-latency routing optimization strategy based on task assignment is proposed.The strategy jointly allocates the transmission data packet size of each path according to the routing resources of the optimal and suboptimal transmission paths in the current network environment.In addition,the SDN controller fully calls the underlying physical resources according to the scenario requirements,adjusts the task transmission path,and improves the adaptability of the power grid.The simulation results show that the proposed multi-path task transmission has lower transmission delay and higher network resource utilization than single-path task transmission and equally divided task transmission.