247 results about "Resource allocation systems" patented technology

The invention relates to the field of engineering management, and discloses a wharf steel structure construction progress dynamic management and control and resource allocation system, which comprises a real-time data perception and fusion module for collecting field data and an initial plan and generating a fusion data stream; the dynamic construction digital twinborn construction and evolution module is used for updating the digital twinborn and a dynamic empirical risk layer in real time based on the fusion data flow; the multi-agent self-adaptive decision engine is used for generating a self-adaptive construction scheme based on digital twinborn simulation deduction and feeding back a risk signal; and the man-machine cooperation and closed-loop execution module is used for visualizing the scheme for manual decision making and issuing an instruction to a site. According to the method, the physical field data sensed in real time is fused with the digital model, the dynamic construction digital twin capable of being synchronously updated with the physical construction field state is constructed, and the technical effect that digital information and the physical entity state are kept highly consistent is achieved.

The invention relates to the technical field of data processing, and provides a train dynamic scheduling method and a resource allocation system, through real-time acquisition and processing of heterogeneous data, generation of train priorities, and generation and verification execution of a scheduling scheme, fine management of a whole train scheduling process is realized, all steps cooperate with one another and are progressive layer by layer, and the scheduling efficiency is improved. Various complex factors in the train running process can be comprehensively considered, the limitation that a traditional dispatching mode depends on experience or a single index is changed, the scientificity, accuracy and timeliness of train dispatching decisions are remarkably improved, resources can be dynamically and efficiently allocated, train running arrangement can be optimized, and the train dispatching efficiency is improved. The transportation efficiency and the service quality are improved, and the ever-increasing diversified requirements of modern railway transportation are effectively met.

The invention relates to a resource allocation system for 5G-A Internet of Vehicles network slices, which belongs to the technical field of intelligent traffic systems and comprises a network slice architecture module, a management and control plane module, a programmable module, a safety and fault-tolerant module, a performance monitoring and optimizing module, a mobility management module, a resource arbitration engine and a cross-domain collaborative interface. And the network slice architecture module is used for dividing Internet of Vehicles communication into a plurality of virtual slices based on a 5G-A network slice technology. According to the resource allocation system and method oriented to the 5G-A Internet of Vehicles network slices, accurate control over end-to-end performance indexes is achieved through the slice definition template library and a QoS dynamic mapping mechanism, the problem that key service performance is degraded due to one-step resource allocation of a traditional network is solved, distributed agent collaboration based on the MAPPO algorithm, and the resource allocation efficiency is improved. LSTM load prediction and a heuristic time delay equalization algorithm are combined, so that the system can respond to business demand changes at a millisecond level, and the resource utilization rate is improved.

The invention discloses a resource allocation method and a resource allocation system in a communication, sensing and calculation integrated Internet of Vehicles system, relates to the technical field of wireless communication, and solves the contradiction of allocation of limited bandwidth and power resources between time delay sensitive type sensing service and large flow type communication service in the existing communication, sensing and calculation enabled Internet of Vehicles. The key points of the scheme are as follows: a communication, sensing and computing integrated Internet of Vehicles system is provided, a resource allocation method in the communication, sensing and computing integrated Internet of Vehicles system is developed, the method particularly focuses on the contradiction between time delay sensitive sensing service and large-flow communication service, and the resource allocation efficiency is improved by combining node association, power and subcarrier block allocation. Optimization among sensing time delay, calculation processing, network stability and communication rate is realized; according to the method, under the condition of ensuring cooperative sensing time delay constraint and sensing precision of cooperative sensing, node association, power and subcarrier block allocation can be reasonably optimized to realize maximization of model training completion degree.

The invention discloses a digital twin auxiliary edge network resource allocation optimization method, and belongs to the technical field of edge computing. Comprising the following steps: establishing a resource allocation system of the digital twin auxiliary edge network; determining transmission time delay and energy consumption required by task calculation in the unloading mode; constructing a multi-intelligent deep reinforcement learning model; and training the multi-intelligence deep reinforcement learning model, and realizing a resource allocation strategy by using the trained multi-intelligence deep reinforcement learning model. According to the method, the service cache module and the task unloading module are established, so that task processing time delay and energy consumption are minimized; the state space of the MEC server and the state space of the user terminal equipment are respectively considered, the task unloading success rate is improved, the task processing time delay and energy consumption are remarkably reduced, and the accuracy of task unloading and resource allocation is further improved.

The invention provides a multi-mode anomaly detection system based on digital twinning, and relates to the technical field of information technologies. Comprising seven main subsystems including a digital twin modeling system, a real-time data acquisition and sensor network, a multi-modal data fusion and processing system, a real-time data analysis and anomaly detection algorithm, a decision support and feedback system, a virtual simulation and visualization system and a safety and compliance management system. The multi-mode anomaly detection system based on digital twinning further comprises six additional subsystems, namely an automatic response and adjustment system, an extensible model updating and management system, an intelligent prediction and early warning system, a deep learning and mode recognition system, a real-time optimization and resource allocation system and an intelligent feedback and user interface optimization system. Through application of a real-time data analysis and anomaly detection algorithm and in combination with a decision support and feedback system, the system can quickly generate decision suggestions or responses, and a decision result is visually displayed through a virtual simulation and visualization system.

The invention discloses a heterogeneous computing resource allocation system and method oriented to collaborative scheduling, the system comprises a resource perception and abstraction module, a collaborative scheduling and allocation module and a dynamic monitoring and feedback optimization module, in the resource perception and abstraction module, network resource state data is calculated and unified measurement conversion is carried out; calculating a comprehensive resource index; the cooperative scheduling and distribution module distributes power grid nodes for tasks according to comprehensive priority values of the tasks, and the dynamic monitoring and feedback optimization module dynamically updates distribution strategies by calculating scheduling effect evaluation indexes. According to the method, for a power grid collaborative scheduling scene, efficient task allocation is realized by establishing a heterogeneous computing resource allocation system integrating resource perception, multi-target optimization and real-time feedback, and efficient operation of a power grid under a complex load is ensured.

The invention discloses a sales resource distribution system based on a dynamic customer portrait, and relates to the technical field of artificial intelligence and big data application, and the system comprises an event modeling module, an abnormity monitoring module, a copy management module, a trial investment evaluation module, an unfreezing control module and an income backflow module. According to the method, a distribution offset map is generated by playing back customer behavior data in historical burst periods, and customer groups and key interaction contacts with easily distorted behaviors are identified as data monitoring references. According to the invention, through dynamic monitoring, label copy management, trial investment feedback evaluation, segmented unfreezing control and a negative pressure backflow mechanism, accurate identification and verification recovery of customer behavior abnormity are realized, the label stability is guaranteed, the sales resource distribution is dynamically optimized, and the response capability and configuration efficiency in an emergent environment are improved.

The invention relates to an intelligent logistics scheduling and resource distribution system based on multi-source data fusion, and relates to the technical field of logistics management technologies, and the system comprises the steps: collecting vehicle operation state data, road condition data, logistics order dynamic data and warehouse inventory change data in real time based on a multi-source heterogeneous interaction platform; constructing a multi-modal traffic logistics time series data set; based on a maximum priority scheduling algorithm, giving priority weights to the logistics orders in combination with logistics order timeliness demands and cargo features; based on the logistics order priority weight, path optimization is carried out by using a space-time hierarchical planning algorithm, and an initial transportation path set is constructed; real-time monitoring of the transportation process is achieved based on the digital twinborn technology, the path condition is sensed dynamically, the optimal transportation path is obtained through continuous adjustment, and an intelligent logistics scheduling and resource allocation scheme based on multi-source data fusion is generated. The method has the advantages that the resource allocation efficiency is improved and the transportation cost is reduced by optimizing the priority path and continuously adjusting the transportation path.

The invention relates to the technical field of communication networks, in particular to a resource allocation system and method in a satellite-ground fusion network, and the system comprises a satellite-ground topology and channel evolution predictor which is used for obtaining satellite ephemeris, user GNSS positioning and moving vectors, ground base station topology and a real-time CQI / RSRP measurement report; generating future link state information; the business QoE impact and switching cost modeling device is used for calculating transient interruption time of a switching action; generating switching cost information; the continuity risk quantification engine is used for generating continuity risk information containing the link maintaining risk probability, the instantaneous impact collapse probability and the link switching risk probability; the risk evasion type resource decision-making device is used for calculating maintenance link comprehensive cost and switching link comprehensive cost; calculating a dynamic switching damping threshold value; generating risk avoidance decision information; according to the invention, the high-frequency ping-pong switching near the edge state point is effectively inhibited, and the signaling overhead caused by invalid switching is reduced.

Embodiments of the present application relate to the technical field of computer storage, and provide a resource allocation method and apparatus, an electronic device, and a storage medium. The method comprises: in response to a memory acquisition request sent by a target host, a memory management unit in a resource allocation system acquiring demanded memory capacity and a memory starting address carried by the memory acquisition request; on the basis of a memory allocation unit in the resource allocation system, selecting from among at least two memory modules a target memory module matching the demanded memory capacity; and on the basis of a memory address router in the memory allocation unit and the memory starting address, performing address translation on the target memory module, and allocating to the target host the target memory module having undergone address translation, thereby achieving dynamic resource allocation of the target host. In this way, the interaction between a memory management unit and a memory allocation unit ensures rapid allocation of idle memory modules in a system, thereby improving the utilization rate of memory resources, and reducing costs of usage of the memory resources.

The invention discloses a server slot resource allocation system and method, a server, equipment and a medium, and relates to the technical field of servers, the system comprises at least one physical slot of the server, a register component and a firmware component, the register component comprises a first register and a second register, the first register is used for storing a global identifier of a physical slot position, determining a resource allocation mode of the physical slot position, configuring a second register at each physical slot position to store a resource allocation parameter of the physical slot position, and reading the first register and the second register by utilizing a firmware component after the server is powered on, according to the resource allocation mode and the resource allocation parameters, resources are allocated to at least one physical slot, on-demand allocation and safe management and control of the resources are achieved, the method is not limited by the slots, the technical problems of resource waste and slot limitation caused by static allocation in related technologies are solved, and the resource allocation efficiency is improved. The technical effects of dynamically allocating resources, remarkably improving the resource utilization rate and deployment flexibility and the like are achieved.

The invention relates to the technical field of network communication, in particular to a 5G-A network slice dynamic adjustment and resource allocation system oriented to low-altitude economy. The system comprises a mobility management feature integration module, a network slice service level protocol evaluation module, a mobility management demand prediction benchmark construction module, a multi-dimensional trend prediction module, a joint optimization decision generation module and a strategy verification and execution module, and is used for acquiring a mobility management feature data set of a wireless network; performing network slice service level protocol evaluation on the wireless network to obtain a network slice state evaluation result; constructing a mobility management demand prediction benchmark; performing multi-dimensional trend analysis on the network slice state evaluation result to obtain a prediction result; performing joint optimization decision on the standard network slice configuration strategy to obtain a network slice adjustment strategy; and executing the verified slice adjustment strategy to realize dynamic adjustment and resource allocation of the network slice. According to the invention, the efficiency of network slice dynamic adjustment and resource allocation can be improved.

The invention relates to the technical field of base station computing power distribution, and particularly provides a 5G base station computing power dynamic prediction and resource distribution system based on digital twinning, and the system comprises a platform computing power total demand prediction module which is used for generating a platform computing power prediction total demand according to a historical operation data set; the user service computing power total demand prediction module is used for generating a user service computing power prediction total demand according to the historical user computing power total demand set; the allocation scheme generation module is used for generating a computing power allocation scheme according to the base station total computing power information, the platform computing power prediction total demand and the user service computing power prediction total demand; the computing power distribution module is used for carrying out computing power distribution on tasks and user services of the digital twin platform according to the computing power distribution scheme; the system can generate a computing power distribution scheme for balancing the computing power requirements of the digital twin platform and the user service by comprehensively considering the total computing power limitation and the predicted requirements of the digital twin platform and the user service on the computing power.

Systems, apparatus and methods are described for dynamic demodulation signal resource allocation. PDSCH / PUSCH DMRS enhancement is provided. A dynamic indication of reference signal functionality may be provided in a slot for an additional DM-RS. A configured CSI-RS / SRS may be dynamically indicated to use as an additional DM-RS in a slot. Frequency shift / hopping of DM-RS as a function of OFDM symbol and / or the order of OFDM symbol containing DM-RS may increase frequency density within a slot. DM-RS antenna port aggregation may increase DM-RS frequency density. One or more DM-RS antenna ports may be used to demodulate the same layer. PDCCH DMRS enhancement is provided. Frequency shift / hopping of PDCCH DMRS may be provided as a function of a REG index within an REG bundle, OFDM symbol index, etc. Use of multiple types of REG (e.g., low and high DM-RS) and REG type may be determined based on subcarrier spacing, operating frequency band, etc.

The invention relates to the technical field of project management, and discloses an infrastructure project resource allocation method and system, and the method comprises the following steps: S1, building resource node classification, and dividing manpower, mechanical equipment, materials, funds and time in an infrastructure project into resource nodes; s2, constructing a resource association model, and defining a mutual relationship among different resource nodes; the invention also discloses an infrastructure project resource allocation system, and the system comprises a resource node classification module which is used for dividing manpower, mechanical equipment, materials, funds and time in an infrastructure project into resource nodes; and a resource association model module. By introducing multi-dimensional resource allocation, self-learning optimization, resource node association and a virtual resource market mechanism, the problems that in the prior art, resource allocation is single, and a dynamic adjustment and resource sharing mechanism is lacked are solved, efficient allocation and dynamic optimization of resources and reasonable utilization of idle resources in an infrastructure project are achieved, and the resource allocation efficiency is improved. And the overall efficiency and the resource utilization rate of the project are improved.

The invention relates to a hierarchical diagnosis and treatment resource allocation system based on an AI priority pre-auditing mechanism, and belongs to the technical field of medical resource allocation, and the system comprises a user input module which is used for receiving initial information of a patient based on an AI applet, and the initial information at least comprises a symptom description, a medical history record, examination data and a diagnosis and treatment stage; the AI intelligent pre-inquiry module is used for performing multiple rounds of questions and answers on the patient according to the initial information to extract an illness state index, inputting the illness state index into a preset risk layering model, and determining an illness state severity / urgency index of the patient; the resource distribution module comprises a special number source pool reserved for experts, and the resource distribution module is used for opening expert numbers for the patients whose illness condition severity / emergency index is greater than an illness condition threshold value; and the referral guidance module is used for recommending a replacement doctor seeing scheme for the patient who does not accord with the open expert number. According to the invention, the technical problem of insufficient fairness and efficiency of an illness state emergency degree registration distribution mechanism caused by structural mismatching of expert resources is solved.

The invention relates to the technical field of data resource allocation, and discloses a cloud-side collaborative data resource allocation method and system, and the method comprises the following steps: 1, firstly, a user submits the information of a calculation task to a cloud-side collaborative resource allocation system in a cloud environment; 2, the system obtains task information; 3, determining how many tasks are processed by the edge node according to the residual resources and task information of the current edge node; 4, resource cost calculation; 5, performing resource allocation on the calculation task according to a decision result of the system task resource decision unit; and step 6, task execution. According to the cloud-edge collaborative data resource allocation method and system, the data processing tasks are intelligently allocated between the cloud and the edge nodes, resource allocation can be dynamically optimized according to the real-time requirements and processing complexity of the tasks, maximum utilization of resources is ensured, resource waste is avoided, and the resource utilization rate is improved. The data transmission delay is low, and the resource utilization rate is high.

The invention discloses a resource allocation system and method based on an MLOps platform, and the system comprises an access controller which obtains a currently executed calculation task, verifies the calculation task, and carries out the access of the calculation task; the scheduler is used for acquiring resource use conditions corresponding to the cluster nodes in multiple dimensions and determining resource load conditions of the cluster nodes according to the resource use conditions; according to the resource load condition, distributing a corresponding cluster node for the calculation task; the control manager is used for managing the execution process of the calculation task; and the command line interface interacts with the user. Through a scheduler, according to a resource load condition, a resource request and limitation of a calculation task (MLOps task) are adjusted, a dynamic resource allocation algorithm is realized, college and optimal utilization of resources are ensured, and full utilization or excessive allocation of resource niches is prevented.

The invention discloses a power communication network resource allocation system and method based on an optical service unit, and relates to the technical field of power communication networks, and the system comprises an infrastructure layer, a transmission mapping layer and a cooperative control layer. Wherein an OSU transmission channel is deployed between the backbone communication network and the power distribution communication network of the infrastructure layer; the transmission mapping layer is deployed with a multi-service priority mapping mechanism and is used for controlling division of service logic, distributing services to corresponding transmission channels and sending service information to the cooperative control layer; a centralized controller and a distributed controller which are in communication interaction are deployed in the cooperative control layer, the centralized controller is used for generating a global resource configuration and path planning strategy of the power communication network according to received service information, and the distributed controller is used for receiving a strategy instruction issued by the centralized controller and sending the strategy instruction to the centralized controller; and the local link state of the power communication network is monitored and dynamically adjusted in real time.

Systems and methods for detecting cardiac events in a patient are described herein. An embodiment of a medical system includes a detection circuit configured to detect cardiac events of the patient at different detection settings using physiologic information of the patient and a control circuit to determine a priority for each detected cardiac event based on the detection setting used to detect the respective cardiac event and to prioritize system resources for the detected cardiac event according to the determined priorities, wherein to prioritize system resources comprises to allocate memory space for the detected cardiac events or to prioritize data transmission of the detected cardiac events to an external system based on the determined priority for each respective cardiac event.

The invention discloses an AI-based deep pulse score remote diagnosis and medical resource allocation system, and relates to the technical field of intelligent medical data security, and the system comprises a data acquisition module which is used for acquiring a deep pulse score diagnosis result of a patient, determining a basic security state of encrypted health data when the encrypted health data is stored in a cloud end, determining dynamic authorization data, and sending the dynamic authorization data to a server; the authorization request processing module is used for acquiring an inter-mechanism sharing request according to the dynamic authorization data, deploying a lightweight smart contract in a block chain network, processing real-time transaction verification logic and generating an authorization confirmation record; according to the AI-based deep pulse score remote diagnosis and medical resource allocation system, a set of intelligent contract-based deep pulse score hosting transaction system is designed on the basis of guaranteeing cloud health data security storage and personalized access authority management, and the trust and efficiency problems of data authorization and sharing among different institutions are effectively solved.

The work breakdown structure (WBS) table in a computerized project management system is modified to include individual columns for each of the resources that is used on a project to produce a scope-resource matrix within the WBS table. The matrix is created when users add each resource directly to a project's WBS table. The users assign the resources to individual tasks and subtasks in the project by adding the allocation level directly the matrix at the intersection of the resource and each task to which the resource is assigned. Also, the computerized project management system automatically reformats selected task rows in the WBS table from their original data field format to a composite operator-data field format when a user adds subtasks to the selected task row. The computerized project management system also allows users to group columns in the WBS table, and the grouped columns can be shown or hidden.

The invention discloses a UAV and USV network resource allocation system and method based on an improved whale algorithm. A constraint condition construction module is used for taking a correlation coefficient between a USV and a UAV, a service duration of providing service for the UAV by the UAV and a processor calculation frequency of the USV as constraint conditions; the optimization problem construction module is used for constructing optimization problems of minimizing USV task processing energy consumption and maximizing USV data processing amount; and the resource allocation module is used for iteratively solving the optimization problem by using the improved whale algorithm to obtain resource allocation between the UAV and the USV network. According to the method, a traditional whale optimization algorithm is fused with a novel coding mode and crossover mutation operation, the problems of poor feasible solution performance, poor convergence and high time complexity in existing resource allocation are solved, and the QoS requirement of intensive tasks is met.

The invention relates to a point cloud multi-scale feature segmentation method and device based on an attention mechanism, equipment and a medium. The method comprises the following steps: constructing a multi-scale feature group by extracting geometric and semantic features of point cloud data, and calculating local geometric complexity and semantic importance based on a real-time strategy to generate a dynamic weight coefficient; the time sequence activation sequence of the multi-scale branches is controlled according to the weight priority, and fine segmentation of the key area is achieved; and finally, strategy parameters are optimized through a closed-loop feedback mechanism, and a self-adaptive scene evolution resource allocation system is formed. According to the method, the problems that a static attention mechanism cannot adapt to scene changes and multi-scale computing resource allocation is unbalanced in the prior art are solved through a dynamic allocation strategy, the segmentation precision and the computing efficiency in a complex dynamic scene are remarkably improved, and reliable technical support is provided for real-time three-dimensional perception scenes such as automatic driving.

The invention relates to the field of software automatic testing and resource compiling and matching, in particular to a virtual-real combined automatic testing resource compiling and matching method and system based on software definition, and the method comprises the steps: receiving a use case script compiled by a user side and a called packaging library basic method, and selecting a use case script execution plug-in; receiving task timing created by the user side and environment variables executed by the test case, and reading environment variable parameters executed by the test case and set by the user side through the case script; receiving a test definition created by a user at an automatic test system end, calling a scheduling tool to process the test definition, and generating a task definition; receiving an execution instruction triggered by a user at an automatic test system end, generating a task instance according to the task definition by calling a scheduling tool, and starting an execution environment to execute a task; and receiving a running result sent by the execution environment, and judging a task execution condition based on the running result.

The invention discloses a cardiovascular nursing medical resource allocation system, and relates to the technical field of medical information, and the system comprises a multi-sensor data collection network which is used for collecting various signal data related to cardiovascular health from a patient and an environment; and the data integration and preprocessing module is used for performing format unification, noise suppression and feature extraction on the original data acquired by the multiple sensors. According to the cardiovascular nursing medical resource allocation system, real-time monitoring and accurate early warning of the cardiovascular state are realized through accurate data acquisition, data preprocessing and mixed deep learning risk assessment technologies; meanwhile, hospital resources are dynamically dispatched through multi-objective optimization and a genetic algorithm, and it is ensured that optimal treatment resources can be rapidly allocated when acute events occur.

A hydropower station multi-module collaborative simulation and management system comprises a collaborative management subsystem, a module simulation subsystem and a communication subsystem. The collaborative management subsystem comprises a data sharing unit, an authentication unit, a simulation coordination unit, an exception monitoring unit and a partition storage unit; the simulation coordination unit controls data interaction and resource distribution among the partition modules, and meanwhile, the simulation coordination unit carries out partition module synchronous management based on time and frequency in the simulation process; and the partition storage unit is used for dynamically adjusting data storage resources. Simulation of independent modules, co-simulation of multiple modules, data sharing and simulation requirements are combined, and co-simulation and data storage planning are carried out based on different simulation modes; through the multi-module co-simulation resource allocation system, the accuracy of simulation of each module is improved, the adaptability of simulation system operation and data storage can be improved, resources are reasonably utilized, and the co-simulation efficiency is improved.

The invention relates to an anti-deadlock resource allocation system and method based on a timetable, the system comprises a trackside resource controller WRC, an ATS scheduling module and a turnout, the ATS scheduling module issues the timetable to the trackside resource controller WRC, the trackside resource controller WRC carries out escape according to the timetable and the turnout to obtain an escape timetable, and the escape timetable is used for sending the timetable to the ATS scheduling module. Resource allocation is determined according to five criteria; when resource conflicts exist, the WRC combines an escape timetable and five criteria, the WRC sequentially carries out arbitration according to the priority degrees from high to low, the WRC obtains resources with the high priority degree and releases resources with the low priority degree, and the process is achieved through the method. According to the method, the timetable is added to a judgment criterion, the escape timetable is obtained by escaping the timetable and the turnout, the train arrival sequence is taken as one of judgment conditions, the train can comply with the arrival sequence of the operation timetable while freely competing for resources, and resource distribution can ensure planning.

Systems and methods for throughput enhancement in non-terrestrial networks (NTNs) using orthogonal cover code (OCC) spreading are discussed. A user equipment (UE) of an NTN that communicates with a base station over a service link of the NTN receives, from the base station, a downlink control information (DCI) that indicates a dynamic uplink grant for a physical uplink shared channel (PUSCH), where the DCI communicates an OCC sequence index; identifies, using the OCC sequence index, a first OCC sequence for the first PUSCH from a set of OCC sequences of an OCC size corresponding to the OCC sequence index; spreads data for the PUSCH into the PUSCH using the first OCC sequence; and sends, to the base station, over the service link, the PUSCH according to the dynamic uplink grant. Cases using configuration information for a configured uplink grant are also discussed. Corresponding base station behaviors are discussed.