5 results about "Resource scarcity" patented technology

This invention discloses an edge-cloud resource allocation method and system, applied in the field of edge-cloud resource allocation technology. The method includes: acquiring real-time operating data of insulators; determining each electric field analysis task and its priority based on anomaly analysis results of the real-time operating data; determining the edge-cloud resource requirements of each electric field analysis task based on the simulation processing results of each task; determining the resource scarcity of the electric field analysis system; determining an initial edge-cloud resource allocation strategy based on the edge-cloud resource requirements and task priorities corresponding to each electric field analysis task; optimizing the initial edge-cloud resource allocation strategy using a multi-objective optimization algorithm to obtain a target edge-cloud allocation strategy; and allocating corresponding edge-side resources and cloud-side resources to each electric field analysis task based on the target edge-cloud allocation strategy. The edge-cloud resource allocation method and system provided by this invention effectively improve the utilization efficiency of edge-cloud resources.

This application belongs to the field of land resource management technology, and discloses an intelligent investment promotion matching system and method based on the entire life cycle of land. The method includes: obtaining actual resource occupancy data of public resources provided by shared infrastructure to resident land parcels within a target area; calculating the resource scarcity value of each public resource based on the actual resource occupancy data and the effective design capacity of the shared infrastructure; correcting the initial resource planning parameters of undeveloped land parcels within the target area using the resource scarcity value to obtain actual resource availability parameters of each public resource; obtaining resource demand information of enterprises to be matched, and evaluating the matching degree between the enterprises to be matched and the undeveloped land parcels in combination with the actual resource availability parameters, so as to output investment promotion matching results; thereby improving the accuracy and effectiveness of investment promotion matching, and providing a more scientific and real-time decision-making basis for park investment promotion and land development.

This application relates to the field of ETL resource optimization technology, specifically to a method, system, equipment, and medium for dynamic resource optimization of ETL pipelines. The method includes: collecting time-series data of the ETL pipeline operating environment, dividing it into time windows, and then standardizing it; generating a linear prediction sequence of system load indicators using a linear load prediction model; generating a coupled prediction sequence of system load indicators using a pre-trained multi-dimensional time-series load prediction model; integrating the two prediction sequences and then performing de-standardization to obtain a comprehensive prediction sequence of the original system load indicators; identifying peak periods, off-peak periods, and periods of abnormal resource scarcity based on the comprehensive prediction sequence of the original system load indicators; and dynamically adjusting and executing the scheduling strategy of ETL tasks based on the identification results. This application achieves automated optimization of ETL pipeline resources and improved system efficiency by collecting multi-source time-series data, combining two models to generate a comprehensive prediction sequence, and dynamically adjusting the scheduling strategy.

This application discloses a resource management method, apparatus, server, and storage medium, belonging to the field of computer technology. The method includes: responding to a target instruction, determining an estimated remaining resource; if the estimated remaining resource is less than the reserved resource, acquiring data from multiple launched inference models across multiple dimensions to obtain multiple sets of data; the reserved resource refers to the resources sufficient for the system to operate normally; based on the multiple sets of data, reducing the number of instances of the multiple inference models and allocating resources for the execution of the target instruction. The method provided by this application can minimize the problem of slow system operation or even crashes due to resource scarcity, and can also reduce the failure to launch new inference models and expand inference model instances, thereby reducing inference request waiting time and improving inference efficiency.

The invention relates to a quantity and price reporting method considering distributed fault risk and adjustable capability scarcity. The method comprises the following steps: calculating the fault probability of distributed resources at the current moment; calculating the clearing power of the distributed resource m in the day-ahead electric energy market; a scarcity factor and the upper adjustable capacity, the lower adjustable capacity and the scarcity price of the distributed resources m in the intra-day stage are calculated; and constructing an intra-day electric energy and auxiliary service market model, and dynamically clearing the power of the resources. According to the method, the operation state of the distributed resources and the action mechanism of the fault characteristics are analyzed, the potential fault risk of the distributed resources is evaluated, dependence on the high-fault-probability resources is reduced, the resource scheduling structure is optimized, and the power supply reliability is improved; through distributed resource scarcity pricing and adjustable capacity evaluation based on marginal cost characteristics, market pricing can reflect the adjustable capacity and the opportunity cost of the resources, and the resources are guided to reasonably participate in different markets.