10results about How to "Improve load balancing" patented technology

The invention provides a power distribution network partition optimization method and system. The method comprises the steps that a non-inductive load characteristic index set is constructed, non-inductive load characteristic indexes are constructed into characteristic vectors, electrical attributes of a power supply unit are constructed into attribute vectors, and then a two-dimensional evaluation model is constructed; obtaining a plurality of candidate partitions based on electrical attributes of the power supply units, calculating a comprehensive evaluation value of each load point and each power supply unit through a two-dimensional evaluation model, distributing each load point to the candidate partitions meeting a preset partition requirement through the comprehensive evaluation value, obtaining a preliminary partition scheme, constructing a global optimization model, and obtaining a final partition scheme; and optimizing each candidate partition to obtain a preliminary partition optimization scheme, constructing a corresponding power flow balance equation, and locally adjusting the preliminary partition optimization scheme to obtain a power distribution network partition optimization scheme so as to optimize the power distribution network partition. According to the invention, multi-dimensional evaluation is carried out on the power distribution network to optimize the reasonability of load division of the power distribution network, so that the operation reliability of the power grid is improved.

The invention provides an optical network multipath resource allocation method, system and device, and the method comprises the steps: obtaining a current preset routing table of an optical network according to each node pair in a current directed graph of the optical network; obtaining a service set comprising a plurality of service flows; inputting the preset routing table and the service set into a preset optical network multi-path resource allocation model, and solving the optical network multi-path resource allocation model based on a preset constraint condition and a gradient descent method to obtain a continuous solution representing the allocation proportion of each service flow on different paths and an integer allocation matrix corresponding to the continuous solution; and performing conversion processing on the integer distribution matrix to obtain a corresponding flow table used for recording the distribution relationship between each service flow and each path resource, and issuing the flow table to each network device. The network load balancing degree can be improved, so that the network throughput is increased, the network time delay is reduced, and the network load balancing is realized.

The application discloses a SAS extender intelligent routing method and system based on GNN. The method comprises the following steps: S1, constructing a path link bipartite graph model; S2, performing load-aware graph neural network inference; S3, path allocation proportional decoding and normalization; S4, strategy compilation and hardware delivery; and S5, closed-loop monitoring and incremental learning optimization. The application realizes load balancing, low delay and globally optimal routing through graph neural network modeling; has the advantages of fast fault self-healing, strong generalization and closed-loop adaptive capacity; and is compatible with the existing SAS protocol, has strong real-time performance and low deployment cost.

This application provides a deployment method, apparatus, electronic device, and storage medium for a hybrid expert model. The hybrid expert model includes multiple transformer modules, each transformer module comprising a normalization layer, a compressed multi-head attention mechanism layer, and a multi-level hierarchical hybrid expert layer. The compressed multi-head attention mechanism layer includes an encoder / decoder, a multi-head attention mechanism module, and a position encoder. The multi-level hierarchical hybrid expert layer includes a multi-level hybrid expert architecture. The deployment method includes: acquiring hardware devices of multiple levels to be deployed; deploying the multi-level hybrid expert architecture in the corresponding levels of the hardware devices according to their hierarchy from high to low; the level of the hybrid expert architecture deployed in lower-level hardware devices is no higher than the level of the hybrid expert architecture deployed in higher-level hardware devices. By deploying the hybrid expert architecture according to the hierarchy of the hardware devices and the hierarchy of the hybrid expert architecture, the utilization of hardware bandwidth at different levels in the cluster is optimized, and the computational performance of the hybrid expert model is improved.

This application provides a message processing method, apparatus, storage medium, and computer device. The method includes: in response to any data core receiving a message to be forwarded, generating a control core scheduling request using the data core and sending it to a target scheduler associated with the data core; using the target scheduler, generating scheduling indication information based on the control core retrieval request and the latest load information fed back by each control core under load feedback conditions, and feeding it back to the data core; using the data core, determining a target control core from multiple control cores based on the scheduling indication information, and distributing the message to be forwarded to a target lock-free queue between the target control core and the data core; and using the target control core, retrieving the message to be forwarded from the target lock-free queue and processing the message.

The invention relates to the field of Internet of Vehicles, in particular to a calculation task allocation method and a control module for a vehicle-road cooperation vehicle formation. The method comprises the following steps: firstly, dynamically updating calculation tasks of a vehicle formation, classifying the calculation tasks and adding label information to form a global task pool; and obtaining residual computing power values of computing power nodes such as a head vehicle, a following vehicle, a road test MEC and a cloud server, and detecting node health degrees to form a multi-source computing power pool. Then predicting a potential task of each calculation task and calculating a calculation power dependency degree and a priority degree; performing basic capability scoring on each computing power node, and screening candidate nodes of which the basic capability scores are higher than a preset value; and finally, performing many-to-many matching on each calculation task and candidate node in the double pools by taking the lowest total execution cost of the calculation task and the overall load balance of the calculation power node as optimization targets. According to the method, the problems of relatively large task delay and unbalanced equipment load caused by unreasonable calculation task allocation in the existing vehicle formation can be solved.

The application discloses a kind of high-low voltage switch cabinet load balancing control method and system, it is related to load control technical field, including: constructing multi-cabinet integrated model, each switch cabinet in switch cabinet group is dynamically monitored, obtains each cabinet state matrix;According to each cabinet state matrix, load prediction equalization adjustment is carried out to switch cabinet group, obtains load adjustment first group;Multi-node load balancing evaluation optimization is carried out to load adjustment first group, obtains load adjustment second group, fault risk prediction is carried out to switch cabinet group, obtains fault risk matrix;According to load adjustment second group, power quality risk prediction is carried out to switch cabinet group, obtains power quality risk matrix;Multi-dimensional optimization is carried out to load adjustment second group, obtains load balancing control strategy.The application solves the technical problem of load imbalance of high-low voltage switch cabinet in the prior art, achieves the technical effect of improving load balancing effect, reducing fault risk and optimizing power quality.

The present application relates to the field of logistics resource management and control, and discloses a logistics resource allocation method, device, equipment and storage medium. The method comprises the following steps: obtaining an initial storage task population corresponding to a to-be-controlled logistics resource; continuously recombining a task individual corresponding to each first storage task by using a preset acceleration genetic strategy until the initial storage task population meets a preset optimization condition, and then stopping the recombination to obtain an optimal storage task population; pre-allocating the to-be-controlled logistics resource to each processing node corresponding to a second storage task by using a preset dynamic allocation strategy to obtain an initial allocation decision sequence of the to-be-controlled logistics resource in each processing node; and stopping the allocation until the initial allocation decision sequence meets an allocation condition, and then taking the initial allocation decision sequence as an optimal allocation decision sequence. The present application realizes cloud storage of logistics resources on multiple general servers, improves the storage utilization of the general servers, and optimizes the system load balancing.

The utility model discloses a balanced thread structure which comprises a base body, a thread and an axial decreasing subtractive material, the thread is formed on the surface of the base body, the axial decreasing subtractive material is at least formed in a screwing area of the thread, and the subtractive quantity of the axial decreasing subtractive material is gradually decreased from the maximum load end of the thread to the minimum load end of the thread in the axial direction of the thread. According to the balanced thread structure, on the premise that basic parameters of standard threads are not changed and axial installation space is not increased, through local axial decreasing and material decreasing, threaded connection load distribution optimization is achieved.

The invention provides a controller fragmentation method, electronic equipment, a computer storage medium and a program product. The method comprises the following steps: the master controller monitors the running states of the plurality of slave controllers; wherein each slave controller is provided with a corresponding fragment label; the main controller obtains a to-be-scheduled custom resource object, wherein the custom resource object is used for describing a user task; the master controller determines a target slave controller from the plurality of slave controllers based on the running state of each slave controller and the attribute of a to-be-scheduled custom resource object; the master controller allocates a fragment label of a target slave controller to the custom resource object to obtain the custom resource object carrying the fragment label; the master controller schedules the custom resource object carrying the fragment label to a target slave controller, so that the target slave controller carries out tuning processing on the custom resource object; therefore, the availability of the system is improved.