8results about How to "Resolve resource conflicts" patented technology

The invention provides a multi-robot task allocation optimization algorithm in an old-age service scene, and the algorithm comprises the steps: building an old-age demand model through a Petri network, and extracting a conflict transition set; forming a genome by the conflict transition set and robot numbers, and randomly generating an initial population; taking the satisfaction degree of the old as a fitness function, and screening chromosomes to obtain a first new population; performing genome interchange variation to obtain a second new population; screening and modifying infeasible solutions by using a Petri net state equation to obtain a third population; and repeating the process to obtain an optimal scheme. By establishing the model based on the elderly needs, the operation process of the elderly service institution can be simulated more accurately, and a reliable reference framework is provided for robot task scheduling. By extracting the conflict transition set, a potential resource conflict problem can be identified and solved in advance, so that the task execution efficiency is improved.

The invention provides a data processing method and device, electronic equipment and a storage medium, and relates to the technical field of telecommunication. The method comprises the following steps: acquiring a physical resource demand of an information technology service and a physical resource demand of a communication technology service; according to the difference of the information technology service and the communication technology service for physical resource demands, determining the deployment mode of the server clusters, the deployment mode of the server clusters including different clusters without sharing servers, the same cluster without sharing servers and the same cluster with sharing servers; physical resources are converted into virtual resources through a virtualization technology, and information technology services and communication technology services are deployed in the virtual resources according to a deployment mode of a server cluster. According to the method, different deployment modes of the server cluster are determined according to the difference of the requirements of the information technology service and the communication technology service for the physical resources, and the virtualization technology is combined, so that the problem of resource conflicts caused by deployment of different services in the same resource pool is solved.

This invention discloses an adaptive load balancing method and system based on multi-dimensional time-series prediction, belonging to the field of communication network technology. The method collects network state information using in-band network telemetry and constructs a matrix, which is then input into a time-series prediction model to obtain predicted values ​​for multiple future time steps. For image streams, an optimization objective is constructed based on available bandwidth and stability measured by the coefficient of variation. An improved whale optimization algorithm is used to search for path weights, dividing the image stream into stream segment units for multi-path forwarding. For mouse streams, the port image stream strength is calculated at the switch end to select the forwarding port, and a fast feedback mechanism is triggered for the first packet. The source end adaptively adjusts the sending window based on queue depth and predicted link utilization. This invention effectively solves the load balancing problem of mixed mouse and image streams in data center networks through prediction-driven differentiated scheduling.

The application discloses an intelligent circuit breaker embedded interface system based on Lvgl and relates to the technical field of power distribution systems.The system is sequentially configured as an application interface layer, a business adaptation layer, an Lvgl customization optimization layer, a device driving layer and a hardware abstraction layer along a data flow direction, and bidirectional data interaction and event linkage are realized through standardized interfaces of the layers.Through the adoption of a five-layer decoupling architecture and the collocation of standardized interfaces, the system realizes the deep decoupling of hardware, driving, GUI and business logic, greatly improves the portability, expandability and maintainability of the system, reduces platform adaptation and subsequent upgrade costs, effectively solves the resource conflict problem of GUI drawing and core business through the customization optimization of Lvgl, guarantees the hard real-time performance of the core business, simultaneously realizes the lightweight and scene-based operation of the interface system, and perfectly adapts to the application requirements of intelligent circuit breaker fault priority and operation and maintenance simplicity.

The application provides a method and system for collaborative optimization of a commercial model of an energy storage power station based on multi-objective programming, relates to the technical field of energy storage power station operation, and comprises the following steps: obtaining a commercial model feature set by performing space-time dimension decoupling on operation data of the energy storage power station; establishing a multi-objective programming constraint system; obtaining a commercial model combination scheme based on a Pareto front search strategy; generating a dispatch execution instruction according to the commercial model combination scheme; and identifying and adjusting the capacity allocation of the commercial model in conflict. The application realizes dynamic collaborative optimization of multiple commercial models of the energy storage power station, and improves economic benefits and operation safety.

This invention provides a method and system for intelligent allocation of computing resources for multi-task parallel training, relating to the field of computing resource management technology. It includes acquiring resource request information such as the computational requirements, storage capacity requirements, and communication bandwidth requirements of multiple tasks to be trained; abstracting computing resources into a resource pool composed of divisible and composable resource atoms; and combining these atoms to form resource quota units with computational capacity and available time indicators. A matching function is established between training tasks and resource quota units to quantify the supply-demand matching degree; a system of resource competition constraint equations is constructed to solve for the optimal allocation scheme, forming initial resource binding relationships and planning execution time slices. After parallel training starts, the resource consumption rate and training progress speed are monitored in real time; when a nonlinear deviation is detected, the resource quota units are dynamically disassembled and reassembled.

The invention discloses a vehicle-mounted-cloud road time health multi-dimensional analysis and risk assessment system, and belongs to a vehicle-mounted analysis and assessment technology. Capacitance, pressure and radar signals are fused, the defect of a single sensor can be overcome, a lightweight self-adaptive filtering model generated based on hardware sensing meta-neural architecture search is adapted to a vehicle-mounted edge computing power constraint and interference feature real-time sensing mechanism, so that the model can adjust a filtering strategy according to vehicle vibration and illumination changes, and the vehicle-mounted edge computing power constraint and interference feature real-time sensing mechanism is optimized. The dynamic scene self-adaptive capability is enhanced, the delay of the generation of the health state snapshot of the edge end can be effectively reduced through model quantification and hardware optimization, and the occupancy rate of vehicle-mounted computing resources can be effectively reduced by unloading a complex model training task to the cloud and only executing lightweight reasoning by the edge end. The parameter updating strategy is dynamically adjusted based on the communication quality, the data transmission amount can be effectively reduced in a weak communication environment, and the model updating failure caused by communication fluctuation is avoided.

The invention discloses a resource scheduling method of a quantum computing measurement and control system and a quantum computer.The resource scheduling method of the quantum computing measurement and control system comprises the steps that whether resource conflicts exist between a quantum computing task to be executed and other quantum computing tasks being executed in a task thread or not is judged through a resource manager; according to the technical scheme, when conflicts exist, the tasks with the conflicts are put into the cache queue, when the conflicts do not exist, the quantum computing tasks to be executed are distributed into the task threads, the problem of resource conflicts possibly occurring when the multiple tasks are to be solved at the same time is effectively solved through the scheme, parallel execution of the multiple quantum computing tasks is achieved, and the execution efficiency of the quantum computing tasks is improved. And the execution efficiency of the quantum computing task in the quantum computing measurement and control system is effectively improved.