90 results about "Virtual queue" patented technology

The invention discloses a fine-grained QoS isolation method and device for NVMe-oF storage, relates to the technical field of data transmission, and mainly aims to solve the problem of tail delay amplification caused by cross-tenant I / O interference in a multi-tenant environment. The method comprises the following steps: acquiring system telemetry data and a multi-tenant I / O request stream in a multi-tenant scene; performing micro-slice processing on the multi-tenant I / O request stream, and importing each obtained micro-slice into a corresponding virtual queue; determining a two-dimensional credit vector for controlling each virtual queue based on the system telemetry data; and on the basis of the two-dimensional credit vector of each virtual queue, performing scheduling and gating release on the micro-slices in each virtual queue on a preset time grid. According to the invention, the micro burst is effectively inhibited at the RNIC near end, the delay amplification path is cut off, the I / O tail delay is reduced, and the service quality predictability in the shared storage environment is improved.

The invention belongs to the field of metallurgical industry automation, and relates to an iron and steel joint enterprise energy management system scheduling method based on Lyapunov optimization and deep reinforcement learning. In order to solve the problems that an existing system depends on static rules or experience, is difficult to adapt to dynamic changes, is low in energy scheduling efficiency and the like, a multi-dimensional state space covering energy storage, a virtual queue and environment parameters is constructed, and a scheduling action space including capacity adjustment, multi-energy medium charging and discharging control and the like is defined; a Lyapunov drift function is introduced as a stability constraint, a reinforcement learning agent of an Actor-Critic framework is constructed, and global energy collaborative optimization is realized in combination with an energy sub-optimization problem solving and parallel sampling mechanism. The method can give consideration to scheduling economy and system stability, has dynamic adaptive ability, ensures project feasibility of the scheme, can improve energy utilization efficiency, reduces cost and carbon emission, and is suitable for iron and steel enterprises of different scales.

The invention discloses an early gastric cancer intelligent screening and risk layering method and system based on multi-modal data fusion and deep learning. The method comprises the following steps: acquiring a gastroscope image, a pathological image, a medical image and clinical data of a patient, performing standardization processing and forming unified feature representation; training the multi-branch neural network model group, and generating a virtual queue tag based on each mode; fusing a multi-modal queue division result to generate a patient comprehensive queue label; adaptively selecting a decision path according to the label, and executing feature fusion and analysis of corresponding depth; generating a structured report containing gastric cancer risk levels and individualized monitoring suggestions; and deploying the system and dynamically tracking the change of a patient queue to realize continuous monitoring of disease progression. Cross-modal semantic alignment, uncertainty evaluation and a Markov prediction model are introduced into the system, the screening accuracy, credibility and dynamic risk evaluation capability are improved, and the system is suitable for early screening and personalized management of gastric cancer.

A method for handling data packets by a communication node in a communication network, the method comprising storing received data packets in at least two physical queues, wherein a first of said at least two physical queues is associated with low latency data packets and a second of said at least two physical queues is associated with high latency data packets, wherein each data packet is stored in one of the at least two physical queues based on a delay characteristic associated with the data packet, for each received data packet, storing an associated information record in at least two virtual queues, VQs, wherein associated information for data packets stored in said high latency physical queue is stored in a second of said at least two virtual queues and wherein associated information for data packets stored in said low latency physical queue is stored in both said first and second of said at least two virtual queues, serving data packets from the at least two physical queues, using at least two Congestion Threshold Values, CTVs, wherein a first of said at least two CTVs is applicable to data packets in said low latency physical queue and wherein both said first and second of said at least two CTVs are applicable to data packets in said low latency physical queue and data packets in said high latency physical queue, wherein said at least two CTVs are used for at least one of dropping and marking packets based on their associated information.

A traceable method for task replication and resource allocation of a large-scale machine type communication network belongs to the technical field of wireless communication and mobile edge computing, and comprises the following steps: based on a Lyapunov optimization theory, establishing physical and virtual queue quantization constraints, and converting long-term optimization into a drift and penalty minimization problem of each time slot; decomposing into task replication, resource block allocation and edge server queue management sub-problems, and sequentially solving; determining an optimal task replication scheme, and storing the optimal task replication scheme as a first decision-making voucher; determining a resource block allocation scheme, and storing the resource block allocation scheme as a second decision-making voucher; determining an optimal edge server queue management scheme which comprises an edge server task processing rate and a task discarding amount, and storing the optimal edge server queue management scheme as a third decision-making voucher; updating a queue state, packaging the decision-making voucher and the queue state into a periodic transaction, writing the periodic transaction into a block chain, and forming an operation auditing log; according to the method, the optimal balance of long-term operation cost is realized, and the decision-making process has traceability.

The invention discloses a dynamic state updating scheduling method in a multi-terminal wireless communication system. The method comprises the following steps of: aiming at the problem that uplink resources are limited, constructing a virtual queue to represent the historical resource use condition of a terminal; dynamic updating indexes are designed to quantify urgency of state updating; high-value terminal screening and an optimal scheduling decision are executed in each time slot; and a Lyapunov optimization framework is creatively combined with a dynamic threshold mechanism. By adopting the method provided by the invention, the average information urgency can be minimized, and the information transmission performance of the system is effectively improved.

The application relates to the technical field of network slices, in particular to a message priority scheduling test system for high-density V2X communication, which comprises a V2X slice congestion state monitoring module, which is used for monitoring the C-V2X message arrival rate and the physical buffer occupancy rate of each network slice, calculating a virtual queue length value, and aggregating the virtual queue length value of all network slices with corresponding slice identifiers. In the application, the C-V2X message arrival rate and the physical buffer occupancy rate of each network slice are synchronously observed and numerically integrated, a slice congestion state representation system with time sensitivity and dynamic adaptability is established, the identification capability for network operation pressure is improved, and through coupling modeling of the message life cycle and the slice bearing state, a potential hazard degree index for a single message is constructed, so that the scheduling system has stronger perceptual granularity and task level discrimination capability.

The application discloses an edge resource allocation method and device based on long-term value fairness and overlapping coalition game, a medium and equipment, and belongs to the technical field of mobile edge computing and resource scheduling. The method builds a distributed crowdsourcing system architecture, establishes an ESP multi-dimensional resource capability, a dynamic task flow and a reputation evaluation model, models the resource collaboration problem as an overlapping coalition game, builds a value loss virtual queue, converts it into a single time slot optimization problem by using a Lyapunov drift plus penalty framework, and designs a distributed potential game algorithm guided by rights and interests to realize the collaborative optimization of system efficiency and long-term fairness.

The invention discloses a network virtualization resource management method and system, and relates to the technical field of intelligent resource management, and the method comprises the steps: initializing an AoL virtual queue, dynamically updating the queue through a Lyapunov drift method, dividing scene feature groups in combination with an ODSS algorithm, fusing prediction results of multiple models, correcting deviation through a Lyapunov-ODSS objective function, and refining the prediction results according to priorities. And an OPT-JR multi-objective function is defined, and an optimal resource allocation vector is solved by using an NSGA-II algorithm. According to the method, the Lyapunov drift theory is introduced to carry out resource regulation and control, the ODSS feature screening algorithm is combined to carry out feature selection, the robustness and real-time performance of resource management are improved, multiple models are fused to carry out collaborative prediction, the precision and stability of resource demand prediction are improved, and the utilization efficiency and intelligent scheduling of resources in a virtualized network are realized.

The application discloses an edge intelligent body flexible scheduling method based on Lyapunov optimization and Stackelberg game. The application constructs a cloud-edge-end three-layer edge intelligent body federated learning network architecture to complete distributed collaborative training under the premise of protecting data privacy. In view of the problems of heterogeneous edge intelligent body network nodes, non-independent and identically distributed data and limited communication resources, a long-term joint optimization model of client selection and bandwidth allocation is established, and model accuracy, time delay and energy consumption are considered. Lyapunov optimization is used to decouple long-term random optimization into real-time decision-making per time slot, and to convert constraints into virtual queue stability control. Dynamic client selection is realized based on Stackelberg game, and high-quality nodes are adaptively selected. Adaptive bandwidth allocation is completed through an evolutionary algorithm, and communication requirements of key clients are preferentially guaranteed. The application can significantly improve model accuracy, reduce time delay and energy consumption, guarantee long-term stability of the system, and is suitable for high-dynamic edge intelligent body federated learning scenes.

The present application relates to the field of distributed large model inference, and particularly relates to a distributed large model inference method based on token perception and Lyapunov optimization. The scheme comprises: after receiving a user input prompt, predicting the output token length of the corresponding task through a length perception semantic module, calculating the corresponding total amount of work, based on the token length prediction result, the real-time state of the device and the long-term virtual queue state, generating a final unloading decision through the Lyapunov guided unloading optimization module iterative unloading algorithm; the client unloads the task to the corresponding cloud edge device according to the final unloading decision, and the device executes the large model inference; the scheduler updates the virtual queue length according to the actual task execution time and the device computing power utilization rate, and provides input for the next time slot decision. The present application is suitable for inference systems utilizing distributed large models.

Location-based virtual queuing of vehicles is described. A request to join a virtual queue may be received from a user application. In response to receiving the request, the server may determine, using a geo-fencing feature, if the user computing device running the user application is within a first predetermined distance of a queue location, where the queue location is a destination of the requesting user vehicle. Then, in response to receiving confirmation that the requesting vehicle user is within the first predetermined distance, the server may automatically create and add a reservation message to a data structure that includes a plurality of reservation messages. Also, in response to the creating the reservation message, the server may provide the requesting user application a notification with the position within a queue managed by the data structure and an estimated wait time that is generated using information stored within the data structure.

Presented are cryptographic digital assets for retail products, methods for making / using such cryptographic digital assets, and computing systems for generating, intermingling, and exchanging blockchain-protected products. A method for provisioning cryptographic digital assets associated with retail product transfers includes broadcasting notifications of a future transaction of a retail product, and receiving, over a distributed computing network from the computing devices of multiple users, requests to participate in the transaction. A select number of users is added to a virtual line associated with the retail product transaction; from the virtual line, a first user is selected to receive the retail product and a second user is selected to receive a cryptographic digital asset containing a digital retail product and a unique digital asset code. The cryptographic digital asset is transferred to the second user's digital wallet, and the unique digital asset code is recorded on a record block of a blockchain ledger.

The application discloses a kind of based on equipment training time fair federated learning method, mainly including the equipment selection method for guaranteeing training time fairness from long-term perspective, and the model aggregation method cooperating with equipment selection method.Federated server selects equipment by means of virtual queue and predicted equipment training time, and selects equipment to participate in each round of training;Selected equipment downloads global model from federated server, trains on local data, and sends back model to federated server after training;After receiving all the returned models, the federated server uses the model aggregation method to aggregate the models;The above process is repeated until the federated learning task is completed.In addition, with the help of training time fairness constraint, the application ensures that all devices can participate in training, while preventing excessive training time.The model aggregation method cooperates with the equipment selection method to increase the weight of the devices that are selected less frequently during aggregation, allowing each device to contribute to the model.

The invention discloses a cross-regional construction site-oriented edge smart center data scheduling method and system, and the method comprises the following steps: receiving construction site heterogeneous data streams, and outputting a hierarchical data stream set; constructing a virtual queue to represent backlog and default risks, and adopting an online optimization mechanism of an SODA algorithm to generate a scheduling strategy; queueing and channelizing the hierarchical data stream set according to a scheduling strategy to obtain a channelized data stream set; based on the channelized data stream set, dynamic degradation is executed according to a scheduling strategy when resources are insufficient, and a degraded data stream set is generated; the switching cost of the degraded data stream set is calculated, and a stable scheduling strategy is obtained; freezing current scheduling execution according to a stable scheduling strategy, and outputting a supplementary transmission task sequence; and performing duplicate removal and selective supplementary transmission on the supplementary transmission task sequence, and outputting an audit record through an auditable replay mechanism. According to the invention, the timeliness guarantee capability and the data consistency of cross-regional data transmission are improved.

The application discloses a fine-grained QoS isolation method and device for NVMe-oF storage, relates to the technical field of data transmission, and mainly solves the problem of tail delay amplification caused by cross-tenant I / O interference in a multi-tenant environment, and the method comprises the following steps: acquiring system telemetry data and multi-tenant I / O request flow in a multi-tenant scenario; performing micro-slicing processing on the multi-tenant I / O request flow, and importing each micro-slice obtained into a corresponding virtual queue; determining a two-dimensional credit vector for controlling each virtual queue based on the system telemetry data; and scheduling and gating the micro-slices in each virtual queue on a preset time grid based on the two-dimensional credit vector of each virtual queue. The application effectively suppresses micro-bursts in the RNIC near end, cuts off the delay amplification path, reduces I / O tail delay, and improves the service quality predictability in a shared storage environment.

An interface module connected to a storage controller and relaying communication between a host and the storage controller. The host and the storage controller use different communication protocols, include computing cores and a memory. At least one of the computing cores is a IO core in communication with the host, each of the IO cores has a virtual queue in the memory and the IO core is configured to execute a reception process of converting communication data including a command to the storage controller outputted by the host into a storage interface command and store the communication data in the virtual queue. The IO core executes a sending process for sending to the host by converting to communication data takes out a storage interface command from the virtual queue, and in same session, same IO core performs the reception process and the transmission process.

The invention relates to a virtual queuing system for managing a virtual queue for a resource, the system comprising a plurality of user devices and a virtual queue management unit, where each user device is configured to: allow a user to join a virtual queue for the resource by creating a virtual queue entry associated with the user device; wherein the virtual queue management unit is configured to: maintain a virtual queue comprising a sequence of virtual queue entries; and manage the virtual queue by sequentially removing virtual queue entries from the virtual queue and providing each user device associated with a removed virtual queue entry with an access pass allowing the user to access the resource; wherein the virtual queue management unit is further configured to: receive user behaviour data associated with one or more virtual queue entries that are within the virtual queue or that have been removed from the virtual queue; and vary the management of the virtual queue in response to the received user behaviour data. By using behaviour data associated with the virtual queue entries the system can more reliably match the supply of users to the actual throughput of the resource so that the capacity of the resource remains saturated while ensuring that a physical queue at the resource does not exceed a desired level.

The present application relates to the technical field of intelligent sorting and industrial process control in coal mine, and particularly relates to a coal gangue intelligent rejection control method based on asynchronous data flow compensation. The technical scheme comprises asynchronous data acquisition, time stamp virtual queue establishment, dynamic space-time mapping, rejection advance calculation, rejection control execution, end feedback measurement, error self-correction, and the asynchronous data acquisition acquires a first data flow and a second data flow respectively, the first data flow is the target category, target coordinates and corresponding time stamp output by an X-ray identification device, and the second data flow is the speed, displacement or beat information and corresponding time stamp output by a belt or cloth device running state detection device. The present application solves the technical problems of asynchronous data registration, space-time dislocation in identification and execution, and time-varying delay compensation of the execution chain in the coal gangue rejection control, and realizes stable, high-precision and self-correctable rejection control of the online coal gangue sorting equipment.

The invention discloses a radiation sensing multi-cell cooperative transmission method and system supporting sustainable URLLC service, and relates to the technical field of wireless communication, and the method comprises the following steps: constructing a system model; based on a system model, a long-term stochastic optimization problem oriented to multiple time slots is constructed by taking minimization of the long-term time average transmitting power of the system as a target; introducing a virtual queue to convert a long-term stochastic optimization problem into a single-slot deterministic optimization sub-model in each scheduling period; determining an incidence relation between each cellular user and the multi-antenna base station through centralized global cooperative matching; and each multi-antenna base station independently solves the self beam forming and subcarrier allocation strategy in a distributed mode, and dynamically and repeatedly executes in a continuous scheduling period to realize multi-cell cooperative data transmission. According to the method, cross-cell joint resource scheduling and long-term stability guarantee are realized aiming at the problems of strong burstiness, interference sensitivity and high centralized optimization cost of the URLLC service.

The embodiment of the invention discloses a data caching circuit and method, a processor, electronic equipment and a chip product, and relates to the technical field of electronics. The data caching circuit comprises a static random access memory (SRAM) which is provided with a plurality of virtual first-in first-out queues; a plurality of input registers for storing valid data sent by an upstream circuit; wherein one input register corresponds to one virtual first-in first-out queue; and the first arbiter is used for determining a first target virtual FIFO queue from the plurality of virtual FIFO queues and controlling effective data in the input register corresponding to the first target virtual FIFO queue to be transmitted to the first target virtual FIFO queue for storage. According to the embodiment, the hardware area can be reduced under the condition of realizing data caching.

A queue management system is provided having a customer device and service provider computing devices in different service provider facilities. The customer device is configured to prompt customers to select a services, receive a customer service request, and facilitate communication between the customer and a service provider in a first service provider facility. The system includes a server that receives availability information for service provider computing devices; generate virtual queues; receives a customer service request from a customer device identifying service type requested; assigns the customer service request to a virtual queue based on the availability information associated with the plurality of service providers and the service type requested; and notifies the customer of the assignment. The server is configured to consider a virtual queue for both an in-person service provider and a remote service provider when determining the virtual queue that the customer should be assigned to.

The embodiment of the invention relates to a virtual machine live migration state recovery method and device for a cross-device model, and the method comprises the steps: carrying out the fuzzy matching based on a PCI address in a device identification character string when a source end device is virtio-blk, a destination end device is vhost-user-blk, and when a destination end QEMU loads a device state, carrying out the fuzzy matching based on the PCI address in the device identification character string; and dynamically binding a state loading function of the vhost-user-blk device to load a device state, analyzing a virtual queue state transmitted by migration to determine a to-be-processed input / output request window, sending descriptor information corresponding to the to-be-processed input / output request window to the SPDK, reconstructing and executing a to-be-processed input / output request by the SPDK, and triggering interruption to complete response. Compatible loading and input / output state consistency recovery of the heterogeneous equipment model can be realized.

A system and method for managing unstructured data stored across multiple data repositories is disclosed. The method includes accessing unstructured data items from distinct data repositories and generating classification metadata for each unstructured data item using a machine learning-based classifier. A residency pointer is generated for each unstructured data item based on residency metadata that identifies its storage location within the data repositories. An unstructured data metafile is automatically constructed for each unstructured data item. Each unstructured data metafile is assigned to one or more virtual queues based on its classification metadata, enabling organized data management. The method further integrates the virtual queues with a web-based data handling interface that facilitates batch operations on unstructured data items stored across the distinct repositories. The disclosed approach improves data classification, retrieval efficiency, and governance of unstructured data without requiring physical relocation of stored data items.

The invention belongs to the technical field of cross-linked polyethylene insulated cables, and particularly relates to a copper core cross-linked polyethylene insulated cable multi-layer stranding control method and system, and the method comprises the steps: collecting multi-source heterogeneous data of a stranding machine key station, and carrying out the time-space alignment of the data collected at different physical positions through a virtual queue mapping mechanism; based on a material work hardening mechanism and a thermal softening effect, a thermal hardening coupling accumulation factor is constructed, and a dynamic springback correction coefficient is constructed in combination with a mold wear trend; inputting the above characteristics into a random forest model to predict the rebound increment of the conductor, and adjusting the traction tension and the twisting speed in a closed-loop manner; and monitoring a prediction residual error through a model failure drift index, and triggering adaptive updating of the model. According to the invention, through fusing physical mechanism characteristics and machine learning, self-adaptive robust control of the whole life cycle is realized, and hidden dangers of insulation eccentricity are eliminated.

The present application relates to a kind of power distribution network heterogeneous networking scheduling method, equipment and medium, belong to power grid communication scheduling technical field, include the following steps: setting the scheduling variable of relay terminal and data transmission time slice variable, construct queue backlog model and output queue backlog;Based on queue backlog, set virtual queue, obtain the space-time state index of relay terminal, and then obtain the matching preference of relay terminal and each channel;Construct the objective function with the minimum space-time state index as target, formulate corresponding constraint condition;Using relay terminal matching algorithm to solve the objective function obtains relay scheduling decision, based on the relay scheduling decision scheduling relay terminal, and using ant algorithm to optimize time slice variable.The present application jointly optimizes relay scheduling and data transmission time slice variable, reduces network average end-to-end queuing delay, improves the performance and stability of power distribution network communication system.

A dynamic adventure-based experience system for an amusement park includes: a memory storing instructions; and a processor configured to execute the instructions to cause the processor to receive user input from a computing device instructing the initiation of a dynamic adventure-based narrative, wherein the dynamic adventure-based narrative includes multiple sets of information. The instructions further cause the processor to: place an identifier associated with the computing device in a virtual queue associated with the narrative endpoint of the amusement park; select an information set from the multiple information sets based on determined parameters, wherein the information set is associated with a requested task; and output the information set to the computing device.

The invention discloses a virtual network card and electronic equipment, and relates to the technical field of computers, the virtual network card comprises a first interface module, a virtual direct memory access module, a virtual network equipment unloading module and a virtual equipment management module; the first interface module supports an extensible input / output virtualization function and is used for expanding the number of virtual ports by utilizing an extensible equipment interface; the virtualized direct memory access module is used for creating and maintaining a virtual queue and establishing data transmission between the virtual queue and a host through a direct memory access interface; the virtual network equipment unloading module is used for transferring a network processing task from a host to a hardware network card; and the virtual equipment management module is used for configuring various parameters of the virtual equipment. According to the invention, the number of virtual ports and the transmission performance of the network card can be greatly improved.