With the advancement of smart IoT system, equipment modeling technology that adapts to the power Internet of Things becomes more and more important. In the power grid system, various types of equipment access processes are not standardized, the collected data format is not uniform, and the data is difficult to share. There is an urgent need to build a set of equipment modeling methods suitable for the power Internet of Things. By comparing traditional equipment modeling methods, we propose the static modeling structure of equipment in the power Internet of Things, and constructs a description method of terminal equipments on the cloud platform; combined with the construction requirements of the smart IoT system, design the Cloud-side collaborative dynamic modeling technology which based on equipment online status management, resource status management, alarm management and application management. At the same time, integrated equipment management methods for static modeling and dynamic modeling are realized in combination with application cases, providing technologies basis for unified device access, unified data transmission, and open sharing of data.
Power Internet of Things [1] is the application of Internet of Things in smart grid. By effectively integrating power system and communication infrastructure resources, the information level of power system and the utilization rate of existing resources are improved. Thus, important technical support is provided for power grid generation, transmission, transformation, distribution and electricity consumption. The Power Internet of Things contains a large number of terminal equipment, which involves the data interaction frequency of 100 million levels per second. Therefore, how to avoid the access of invalid data is an important topic in the construction process of power Internet of Things. In response to the detection requirements of abnormal devices, this paper, based on existing Intelligent IoT System architecture, designs a real-time detection framework that integrates a two-level control mechanism, which is universal, extensible, and supports multiple protocols, using the data interaction specifications formulated by the State Grid Corporation as the basic detection basis. As a result, the framework realizes the effective interception of abnormal devices in power Internet of Things.
Dynamic load balancing is an important way to improve the resource utilization and parallel computing performance of multi-server system. For the mass of terminals under the Internet of Things scenario high frequency periodic escalation and receiving messages scene, the terminal equipment and message server need to establish a TCP long connection to communicate, the accumulation of messages different degree of weight will cause the load tilt. In this paper, an algorithm based on the socket buffer feedback mechanism is proposed, which takes the server load (CPU, memory, connection rate and socket buffer cache) as the load indicator, collects the load indicator through the load agent and calculates the discrete coefficient of the server socket buffer. The dispatch controller calculates the weight of each server, and the higher the weight, the lighter the server load. The experiments show that the CMTS more realistically feedbacks the server load status than the least connections. As the number of cluster server connections and message sending rate increase, the average cluster response time is shorter.
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