6results about How to "Avoid utilization" patented technology

The invention provides an automatic operation and maintenance scheduling system and method in a cloud computing environment. The method comprises the following steps: predicting a load demand curve through historical load time sequence data and real-time load indexes of an online service cluster; generating an arbitration decision of resource operation and maintenance scheduling according to the simulated resource occupation contour of the online service cluster constructed by the load demand curve and the resource request queue corresponding to the offline task cluster; issuing a reserved resource permission to the second control ring by the arbitration decision, and injecting a virtual node resource view complementary with the reserved resource permission in time and space into the first control ring; and when the real-time load index triggers the first control ring to perform resource scaling operation, the first control ring executes instance scaling in a resource boundary limited by the virtual node resource view, and the second control ring starts and stops the offline task instance in the corresponding resource block according to the current reserved resource permission. According to the technical scheme provided by the invention, collaborative scheduling of operation and maintenance of the online service cluster and the offline task cluster can be realized under load fluctuation.

The invention provides a data processing method, electronic equipment, a storage medium and a program product, relates to the technical field of data management, and is used for predicting the scheduling condition of team members under the condition of given data. The method comprises the steps of obtaining first data input by a user; the first data comprises scheduling information of each member in the target team in a first time period; determining target data based on the first data; the target data comprises the scheduling quantity of the target personnel in the first time period; the target person represents any member in the target team; and based on the target data, determining the total number of schedules of all members in the target team in the first time period.

This application provides an automated operation and maintenance scheduling system and method in a cloud computing environment. It predicts load demand curves using historical load time-series data and real-time load metrics of online business clusters. The simulated resource occupancy profile of the online business cluster, constructed from the load demand curve, and the corresponding resource request queues of the offline task cluster generate an arbitration decision for resource operation and maintenance scheduling. The arbitration decision issues reserved resource licenses to the second control ring and injects virtual node resource views that are complementary to the reserved resource licenses in time and space into the first control ring. When real-time load metrics trigger resource scaling operations in the first control ring, the first control ring performs instance scaling within the resource boundaries defined by the virtual node resource views, and the second control ring starts and stops offline task instances within the corresponding resource blocks based on the current reserved resource licenses. The technical solution provided in this application can achieve collaborative scheduling of operation and maintenance for online business clusters and offline task clusters under load fluctuations.

The present application relates to a kind of high-efficiency impact jet heat exchange method for energy saving and emission reduction using back pressure effect, which is based on jet speed measuring experimental device, the jet speed measuring experimental device includes support, fan, PIV system and glass plate, comprising the following steps: S1, the establishment of physical model, the division of grid, the setting of boundary condition and the setting of working condition parameter, using computational fluid dynamics (CFD) solver to study the back pressure distribution in the flow field when the Reynolds number (Re) range is 3462-6125 and the normalized spacing H / D is 0.25, and the simulation data curve is obtained;The present application can save the physical space of cooling process when in use, greatly reduce the energy consumption cost and exhaust emission of electricity, and further greatly improve the heat exchange efficiency, therefore, the reasonable use of back pressure effect saves the production cost of enterprise, also improves productivity while achieving the effect of energy saving and emission reduction, avoids the problems of low heat exchange efficiency and low energy utilization rate of existing cooling process.

This application provides a service processing method and an electronic device; the method includes: acquiring a first service; generating a first job based on user interest information of a first user associated with the first service, service scenario information of the first service, and performance information of a server cluster; wherein the first job is used to instruct a target server to execute the first service; and executing the first job. This application enables efficient utilization of resources.

The invention provides a standing tree total, overground and underground biomass simultaneous modeling automatic generation method oriented to compatibility constraint, and relates to the technical field of forestry metrology. The method comprises the following steps: constructing an observation mask and a sample weight descriptor, explicitly modeling an addition relation between total biomass and overground and underground biomass into a compatibility constraint calculation graph, and automatically generating a candidate simultaneous model set under unified topological constraints; furthermore, by constructing a simultaneous objective function constrained by compatibility and executing unified parameter estimation, quantitative evaluation and optimization selection are performed on candidate simultaneous models, and finally a deployable model product including a model structure, a parameter file, an input field specification and a prediction interface definition is generated. According to the method, the consistency of the prediction result in numerical and physical significance can be ensured, the stability, the automation degree and the engineering applicability of stumpage biomass modeling are improved, and the method is suitable for application scenes such as forest resource monitoring and carbon reserve assessment.