23 results about "Multi resource" patented technology

The application discloses a kind of distributed reservation systems and methods for multi-resource cooperation, comprising: transaction manager, at least two resource managers, lock manager, transaction log module and workflow controller;Transaction manager coordinates each resource manager through two-phase commit 2PC protocol, realizes the atomicity execution of cross-node shadow and summary table update;Lock manager adopts read-write lock separation mechanism to resolve concurrent conflict, and handles deadlock problem through timeout detection and active unlocking strategy;Transaction log module is based on prewrite log mechanism Complete record shadow and summary table linkage operation details, provide reliable support for fault recovery and transaction rollback;Workflow controller encapsulates distributed call details, realizes service survival real-time detection and automatic reconnection function.The application has high expansibility, strong consistency, high concurrent adaptation capability and perfect exception fault-tolerant mechanism, and can be widely applied to travel service scene of multi-node deployment.

Logic to generate a 320 megahertz (MHz) extremely high throughput (EHT) physical layer protocol data unit (PPDU) comprising a multi-resource unit (MRU). Logic to generation of a non-orthogonal frequency division multiple access (non-OFDMA) 320 MHz EHT PPDU, wherein the MRU comprises a 240 MHz multi-MRU, the 240 MHz MRU comprising at least two contiguous 996 tone resource units (RUs). Logic to generation of an OFDMA 320 MHz EHT PPDU, wherein the MRU comprises at least one 996 tone RU and one 484 tone RU. Logic to cause the transmission of the 320 MHz EHT PPDU. And logic to receive and decode the 320 MHz EHT PPDU.

The application discloses a kind of ground-based radar multi-resource adaptive joint scheduling methods for high-speed target, first in noise and clutter background, ground-based radar system receives and carries out signal processing to the echo in detection airspace, obtains the plot information of detection airspace, then the plot velocity of each wave position is analyzed, then the wave position that appears cross-range cell walk phenomenon calculates the cross-cell walk energy loss coefficient of high-speed target and constructs multi-resource optimization function, finally the adaptive scheduling result of space-time resource and false alarm probability resource is obtained by using CVX toolbox solution, until the overall target detection process is completed.The method of the application considers the energy loss caused by high-speed target range migration, and combines ground-based radar multi-resource cooperative scheduling, realizes the reasonable use of resources while improving the detection performance, the detection performance of high-speed target in clutter and noise environment is significantly improved, and the adaptive optimization of multi-resource cooperative scheduling is realized.

This invention discloses an optimized scheduling method for virtual power plants with multiple resource types, belonging to the field of virtual power plant technology. This method aims to solve the technical challenges of delayed scheduling response due to the strong volatility of distributed resource output, insufficient adaptability to multiple scenarios, and weak distribution network resilience under renewable energy access. The method establishes a multi-resource power adjustable range model based on real-time data, uses linear scaling and displacement algorithms to generate aggregated power domain boundaries, and adjusts the weights according to the different target types of the virtual power plant. It combines ridge regression conditional expectation correction and sub-Bruker optimization to construct a dynamic risk budget, optimizing generation plans and reserve capacity in the day-ahead phase. In the real-time phase, it responds in stages according to power deviation levels, triggering rapid energy storage compensation or emergency interruption of controllable loads. The model parameters are iteratively corrected through a closed-loop feedback mechanism. This method significantly improves the response accuracy and reliability of virtual power plants in frequency regulation, peak shaving, and self-balancing scenarios.

Embodiments of this application disclose a multi-resource-unit transmission indication method, and a related device. The method includes: A first device generates an EHT TB PPDU, where the EHT TB PPDU includes a resource unit indication field, the resource unit indication field is used to indicate a first resource unit used by the first device to transmit the EHT TB PPDU, and the first resource unit is included in a resource unit allocated to the first device; and the first device sends the EHT TB PPDU to a second device. In the embodiments of this application, the RU used by the first device to actually transmit the EHT TB PPDU can be indicated. The technical solution provided in this application may be applied to an 802.11ax Wi-Fi system, an 802.11be Wi-Fi system, or the like.

The present application belongs to the field of computer simulation and optimization algorithm, and relates to a multi-task cooperative scheduling and resource optimization method and system based on slime algorithm. The method comprises: constructing a multi-task and multi-resource cooperative scheduling model, establishing the allocation relationship between tasks and resources, and introducing time window constraints, resource capacity constraints and task priority constraints; encoding the scheduling scheme to represent it, and mapping it into a searchable solution space; constructing a multi-objective optimization model containing task completion time, running cost and resource energy consumption, and realizing multi-objective coordinated optimization through dynamic weight; using slime algorithm for iterative solution, optimizing the scheduling scheme through fitness evaluation, weight updating and position adjustment, and improving the solution performance by combining adaptive parameter adjustment and random disturbance; and outputting the optimal or near-optimal scheduling scheme after meeting the termination condition. The present application can improve resource utilization efficiency and scheduling performance, and is suitable for complex system scheduling optimization.

The application discloses a kind of SDN multi-resource pool authentication method, device, equipment, medium and product, the method includes when detecting that target user selects target resource pool, with the authority check request of resource pool information of target resource pool is sent to authentication service;When receiving the authority check result that authentication service returns after receiving authority check request, if authority check result passes, then allow switching to target resource pool;With the operation request of resource pool information is sent to target service of target resource pool;When receiving the operation result that target service executes operation request after operation request is authenticated, operation result is presented to target user.The multi-resource pool is introduced, and resource pool information is carried in the request to be sent to the service in corresponding resource pool to complete authentication, can take the microservice in the range of multi-resource pool as the authentication object, realize resource pool extensible, increase the authority division of resource pool granularity, and enrich the level of authority management.

Disclosed are a computer-implemented method and a computer-implemented system for orchestrating hybrid quantum-classical execution between high-performance computing (HPC) infrastructure and one or more quantum processors (QPU). An orchestration module breaks down a work flow into subtasks and, for each subtask, compiles multiresource HPC and QPU processing telemetrics, normalises same to a canonical vector and evaluates proposed plans under hard budget constraints (time, executions, cost and / or depth). The system automatically selects an execution resource (HPC or QPU) and, when executed in an QPU, applies tiered error mitigation and verifies the result using an acceptance gate. In the event of rejection, the system executes a deterministic recovery policy with retry, execution resource switching and / or backup routing to HPC. An auditable record of decisions and metrics is generated for traceability and feedback.

This patent discloses a scheduling control method and system for assembly lines based on continuous state evolution, applicable to complex assembly lines under multi-process and multi-resource constraints. The method first continuously models the execution conditions of assembly processes, forming a state expression that reflects the executability of the processes. Based on this, a scheduling focus is constructed according to the current main constraints of the production line, guiding the overall direction of scheduling decisions. Simultaneously, the assembly quality state is introduced into the scheduling state system in the form of reliability decay, allowing quality factors to participate in state evolution during the scheduling process. During scheduling operation, the system forms an ordered execution sequence and generates scheduling instructions. After the scheduling instructions are issued to the execution layer, their execution feedback drives the continuous updating of relevant states, thus forming a closed-loop scheduling control process. Through the above methods, adaptive adjustment of scheduling decisions is achieved, improving the operational stability and scheduling efficiency of the assembly line under complex constraints.

The application provides a hardware device configuration test method and device, wherein the application realizes unified distribution of hardware configuration test data in a large-scale hardware scene with multiple resource pools by using a distributed architecture, improves hardware configuration test data import efficiency, and reduces data maintenance cost. In addition, while multiple modules cooperate to complete hardware configuration testing, each business function module can be independently operated by being decoupled from each other, so that the system modules can be flexibly plugged in and plugged out for different device configuration test scenes; meanwhile, each module continuously and cyclically executes each round of configuration or test at a specific time interval, realizes (quasi-) real-time update of device configuration, and achieves the effect of continuously fitting the device to the desired state. In addition, the application can realize self-identification of a local server to a resource pool, pulling of hardware configuration test data corresponding to the resource pool, and completion of hardware device configuration testing, greatly reducing the manual workload while ensuring the accuracy of related links.

This invention discloses apparatus, methods, and systems for configuring multiple resource allocation modes. One method (400) includes receiving (402) information indicating multiple resource allocation mode configurations. Each resource allocation mode configuration corresponds to a logical channel among multiple logical channels. The method (400) includes determining (404) multiple data transmission scheduling modes for the multiple logical channels. Based on the resource allocation mode configurations for the logical channels among the multiple logical channels, each data transmission scheduling mode corresponds to that logical channel, and each data transmission scheduling mode includes: a first scheduling mode; a second scheduling mode different from the first scheduling mode; or a third scheduling mode including the first scheduling mode and the second scheduling mode. The method (400) includes transmitting (406) a buffer status report based on the multiple data transmission scheduling modes.

The present disclosure provides a method and device for generating a K8S-based node resource portrait, wherein the method comprises: collecting real-time data and historical data of node resources from a k8s cluster and a related system of the k8s cluster; extracting multi-resource dimension features and time dimension features from the real-time data and the historical data; and generating a dynamically updated resource portrait for each node based on the multi-resource dimension features and the time dimension features, thereby solving the problem of lack of comprehensive evaluation of multi-resource dimensions for nodes in the related art.

This invention provides a method, apparatus, device, and medium for replica migration in a distributed storage system. The method includes: responding to a replica migration task triggered by a monitoring system, determining the source location of the data migration based on the source replica; determining the planned storage location of the source replica in the distributed storage system to obtain the target location; based on a pre-set global resource locking order, sequentially requesting resource locks for concurrent control of multiple different types of resources associated with the source location, and sequentially requesting resource locks for concurrent control of multiple different types of resources associated with the target location; and migrating the source replica to the target location if all required resource locks are successfully obtained for the replica migration task. This invention introduces a mechanism based on a global order and multi-type resource collaborative locking, achieving fine-grained concurrent control of the data migration task across multiple resource dimensions.

This application provides a method for coordinating and optimizing a series-type low-voltage DC remote power supply system with multiple resources and time scales. The method includes: constructing a mathematical model of the series-type low-voltage DC remote power supply system; acquiring various adjustable resources of the distribution network; based on the mathematical model of the series-type low-voltage DC remote power supply system and the various adjustable resources of the distribution network, constructing a day-ahead-intraday rolling-real-time optimization model for coordinating the series-type low-voltage DC remote power supply system with multiple flexible resources of the distribution network; and solving the day-ahead-intraday rolling-real-time optimization model to determine a multi-time-scale, multi-resource coordination optimization scheme. The method proposed in this application can effectively solve the low-voltage problem for end users by coordinating other flexible resources of the distribution network with the low-voltage DC remote power supply system, and effectively reduce network losses, ultimately achieving the goal of overall economic, safe, and reliable system operation.

This invention belongs to the field of power automation technology and discloses a method and related apparatus for dynamically constructing a multi-level control unit considering multiple resources. The method includes: acquiring a power grid control scenario; dynamically determining the resource aggregation range based on the power grid control scenario; screening the resource aggregation range to obtain an optimized resource set; constructing a multi-resource optimization combination model with the goal of minimizing regulation costs; and solving the multi-resource optimization combination model based on the optimized resource set to obtain a multi-level control unit considering multiple resources. On the one hand, this invention fully considers the differences in regulation characteristics among multiple resources and utilizes their spatiotemporal complementary characteristics for optimized combination, fully exploring and utilizing the regulation potential of multiple resources. On the other hand, it dynamically screens resources for different control scenarios, ensuring that the multi-resource optimization combination model constructed by this method meets the technical constraints of the corresponding scenarios in terms of technical performance, better supporting power grid control and operation decisions.

The application discloses a kind of ship selective maintenance decision-making method under the condition of multi-resource constraint multi-stage task, comprising the following steps: step A: constructing ship multi-stage task description model;Step B: constructing ship equipment reliability model;Step C: constructing ship maintenance decision-making model framework;Step D: based on ship maintenance decision-making model, solve maintenance scheme.The application also discloses a kind of ship selective maintenance decision-making system under the condition of multi-resource constraint multi-stage task.The application provides scientific basis for subsequent ship selective maintenance decision-making, guarantees the successful execution of maintenance task, and can be widely applied in the field of digital technology.

The application relates to the technical field of edge computing, and discloses a multi-resource cooperative scheduling optimization method in a cloud computing environment, which comprises the following steps: characterizing the resource state of a heterogeneous edge node as a representation point on a discrete state manifold, modeling a computing task as a cooperative hyperedge connected with all participating nodes, and using a potential function attached to the hyperedge to quantify a nonlinear coupling cost; a discrete state manifold and a cooperative hypergraph model are constructed, and discrete gradient optimization is performed on the manifold of each node in the discrete state manifold and the cooperative hypergraph model; the associated nodes in each hyperedge perform distributed potential game with the aim of minimizing the potential function; the optimization instructions of all nodes are harmonized by using discrete Hodge decomposition, and global consistent system state update instructions are generated; the instructions are analyzed into specific resource allocation and task offloading strategies, and are executed, effectively solving the problem that the nonlinear coupling cost is difficult to quantify and optimize in cross-domain edge cooperation, and improving the overall efficiency and decision feasibility of the system.

The present invention relates to a video decoding method. [Solution] The video decoding method according to this document includes the steps of: configuring an MPM (Most Probable Mode) list that includes candidate intra-prediction modes for the current block; deriving the intra-prediction mode for the current block from the MPM list based on MPM index information that indicates the intra-prediction mode for the current block from among the candidate intra-prediction modes included in the MPM list; generating a prediction sample for the current block based on the intra-prediction mode; and generating a restored picture for the current block based on the prediction sample, wherein the step of configuring the MPM list is characterized in that, based on the case where the value of the reference line index information indicating the reference line used for intra-prediction of the current block is not 0, the DC mode is derived as one of the candidate intra-prediction modes and included in the MPM list.

This invention discloses a dual-cycle collaborative scheduling method, system, equipment, and medium for sea-rail intermodal AGVs, comprising: constructing a multi-resource collaborative scheduling model with minimizing completion time as the objective, setting train arrival time as a dynamic trigger parameter; judging the execution timing of direct-fetch tasks based on this, splitting them into sub-tasks from shore to yard and then to train if the arrival time is earlier, otherwise maintaining direct-fetch; constructing dual-cycle constraints in time periods and matching import and export tasks to generate operation sequences; finally, through multi-layer coding mapping, using an improved whale algorithm to iteratively solve and output the optimal scheduling scheme. This invention significantly improves equipment utilization, operation continuity, and overall system scheduling efficiency under the sea-rail intermodal mixed operation mode.