Energy big data acquisition and application based on service portfolio quality

Based on the Web service composition technology, the method of decomposing the quality of QoS indicators is proposed. Compared with the traditional integer programming and genetic algorithm, it improves the calculation speed of QoS of Internet of Things service portfolio quality. Big data technology is an important technology for handling massive amounts of data in a complex network environment. Although the previous big data technology can effectively deal with this, there are still shortcomings in accuracy and real-time. In order to achieve visual energy management and control and improve the application value of big data technology, a real-time visualized integrated energy big data platform based on heterogeneous computers is proposed. The platform can connect to heterogeneous computers of users in the business area in a non-intrusive manner. In order to obtain more accurate data related to energy supply, so as to monitor the state of energy supply from a comprehensive perspective. At the same time, in-depth research on the data resource sharing relationship, value network and service model has been carried out, and corresponding construction methods have been proposed. The results show that the proposed method is faster and more accurate in real-time detection of energy consumption.

Automated summary

The study proposes a method of decomposing the quality of QoS indicators based on Web service composition technology, which improves the calculation speed of QoS for Internet of Things service quality. Research also shows that while big data technology can effectively handle massive amounts of data, there are still limitations in accuracy and real-time processing. Therefore, a real-time visualized integrated energy big data platform based on heterogeneous computers is introduced to achieve visual energy management and control.