14 results about "Concurrent user" patented technology

The invention discloses a software performance test system, method and device in a high-concurrency scene, and relates to the field of software testing, the system comprises a scene intelligent construction module used for generating a concurrency scene through a behavior tree modeling and time sequence prediction algorithm according to service demand parameters and historical traffic data; the distributed test environment scheduling module is used for constructing a distributed test environment by adopting a container arrangement technology; the virtual user load generation module is used for simulating concurrent user requests by adopting a coroutine pool technology; the real-time performance data acquisition module is used for acquiring multi-source performance data of the tested software in real time; the intelligent performance analysis module is used for calculating a core performance index according to the multi-source performance data and carrying out anomaly detection and trend prediction; and the performance bottleneck positioning module is used for mining a dependency relationship among the core performance indexes and generating a bottleneck positioning report and an optimization suggestion document. According to the method, the accuracy, the efficiency and the stability of software performance testing in a high-concurrency scene are improved.

This invention discloses a data model-driven digital human emotion guidance method, belonging to the fields of artificial intelligence and human-computer interaction. It extracts emotional features from speech and text separately using a lightweight gated convolutional network and a pre-trained model incorporating multi-head self-attention, and aligns emotional semantics using a cross-modal attention mechanism to obtain fused features. Based on these features, user emotions are identified, and emotional guidance instructions are generated using a knowledge base to drive the digital human to output emotional voice feedback. Efficient message synchronization in high-concurrency scenarios is achieved through a NATS message middleware based on a publish / subscribe model, and a dual-mode approach is introduced to ensure interaction continuity. This invention significantly improves the accuracy of emotion recognition and the naturalness of feedback, while achieving extremely low CPU utilization and high network throughput with limited hardware resources, stably supporting tens of thousands of concurrent users.

This invention provides a system and method for verifying system interfaces based on artificial intelligence, relating to the field of interface verification technology. The method includes: acquiring historical concurrent user counts, historical system performance data, and historical load impact data; acquiring system interface architecture data and historical system interface architecture data; acquiring real-time load impact data; determining a concurrent user count relationship function based on historical concurrent user counts and historical load impact data; determining the predicted concurrent user count for a prediction period based on the real-time load impact data and the concurrent user count relationship function; obtaining a trained system performance prediction model; processing the predicted concurrent user counts and system interface architecture data according to the trained system performance prediction model to obtain predicted system performance coefficients; and generating a system interface verification report based on the predicted system performance coefficients. According to this invention, the accuracy of system interface verification can be improved.

The invention provides an applet high-concurrency request processing method and system, and relates to the technical field of computer data. The method comprises the following steps: firstly, receiving a high-concurrency user request from an applet front end to generate request feature information; secondly, inputting the request feature information into a pre-trained shunting model, identifying a service type, and marking a user request according to an obtained identification result to obtain a target request stream; inputting the target request stream into a cache decision module, and processing the target request stream according to a determined cache hierarchy corresponding to the user request to output a cache result; inputting the cache result and a preset system load parameter into a load balancer to generate a resource scheduling instruction; and finally, according to the target request stream, the cache result and the resource scheduling instruction, performing cooperative processing on the user request in the target scene. According to the technical scheme provided by the invention, accurate and efficient processing of user requests and adaptive optimization of system resources in a high-concurrency scene are realized.

The embodiment of the invention provides a resource allocation method and device, a storage medium and a program product. In the method, a resource display page pointed by an access link published by an online transaction platform is displayed, a resource participation request is initiated, and multi-source behavior data of users are uploaded, so that the platform identifies participation willingness information and screens candidate users, the scale of the users participating in resource allocation concurrently by the platform is reasonably controlled, and stable operation of the platform is guaranteed; after a user is selected as a candidate, platform page resource information can be received, and an interactive dynamic page containing a resource allocation control and options is rendered and displayed; in resource allocation, a latest resource allocation option regenerated by a platform based on a seller negotiation reference value is received, a page option is updated, a new round of resource allocation request is initiated in response to user operation, irrational and tentative operation of a user is effectively avoided based on accurate interaction with the platform, invalid resource allocation requests are reduced, sharp increase of a quotation round is restrained, and resource allocation efficiency is improved. The high-concurrency pressure of the platform is relieved, and stable operation of the platform is further guaranteed.

An apparatus and method for generating an interactive graphical user interface are disclosed. The apparatus includes a memory communicatively connected to at least a processor, wherein the memory contains instructions configuring the at least a processor to receive first input data and second input data, identify at least a target datum from the first input data, determine at least an operating parameter from the second input data as a function of the at least a target datum, generate a plurality of tasks as a function of the at least an operating parameter, generate an interactive graphical user interface, wherein generating the interactive graphical user interface includes receiving concurrent user actions for the plurality of task nodes from a plurality of user devices and updating the interactive graphical user interface as a function of the concurrent user actions using an adaptive mechanism.

To improve the number of concurrent users. [Solution] The terminal of the present invention includes a receiving unit that receives any of the following signals: a plurality of downlink signals, a first uplink signal from another terminal, and a sidelink signal from the other terminal; and a control unit that reports the measurement result of the first uplink signal and controls the transmission of the uplink channel using the other terminal using the resources based on the report.

The invention provides a method and a device for detecting a conflict of a multi-level structure of a client page, and relates to the technical field of UI (User Interface) testing. The method comprises the steps that a multi-device multi-system test cluster and a cross-platform test framework are built, the cross-platform test framework is integrated with a rule engine, and the rule engine is used for configuring a hierarchical priority rule; generating a multi-level combined scene based on a level component type and a level priority rule, and injecting a dynamic behavior triggered by a simulation user interaction operation and a plurality of extreme scenes to generate a dynamic test scene; based on a dynamic test scene, simulating concurrent user operation in a multi-device multi-system test cluster, verifying event distribution logic, and synchronously managing, controlling and recording rendering data; based on the rendering data, verifying hierarchy rationality from a Z-axis hierarchy, a display time sequence and a focus state three-dimensionally to obtain a verification result; and generating and outputting a three-dimensional conflict positioning report based on a verification result. And full-scene automatic detection of complex page multi-level conflicts is realized.

The application discloses a kind of distributed flow table item effective time dynamic hopping implementation methods, including distributed flow table item effective time dynamic hopping definition, implementation, and balance security, performance and resource consumption three features such as characteristic.This method, flow table item in flow table existence time is regarded as privacy, through the ladder random response mechanism of differential privacy in SDN forwarding equipment local flow table item in flow table existence time is dynamically disturbed, forms dynamic mobile flow table item attack surface, makes low-speed flow table overflow attack unable to synchronize flow table item attack surface, to the attack has realized effective active defense.The method does not need to upgrade existing SDN interface protocol and controller software, does not need to introduce trusted third party, while considering network security, guarantee network performance and expansibility, especially suitable for various types of need to support high security and large concurrent user, and has special requirements to delay and expansibility, guarantee its service quality and user experience.

The application relates to the technical field of data processing, in particular to a layered architecture system for pressure testing of an MQTT protocol and an implementation method thereof. The layered architecture system comprises an interface layer, a business layer, a protocol layer and a network layer. The application adopts a pressure testing thread pool to execute a pressure testing task. Compared with JMeter which simulates the number of concurrent users through the number of threads, the application can effectively avoid the problem that the pressure testing result fluctuates too much due to the uncertainty of CPU scheduling of an operating system caused by a large number of threads, and can effectively reduce the performance overhead of the operating system. The layered architecture system design concept can be applicable to complex IM business scenarios, can support a configurable custom extension I / O framework, and can realize pressure testing requirements in multiple business scenarios and improve the scalability of the layered architecture system through pressure testing request parameter configuration and I / O framework switching configuration.

The embodiment of the specification discloses a kind of knowledge base document concurrent processing method, equipment and medium, it is related to distributed computing technical field, method includes: receiving multiple concurrent user requests by asynchronous network interface, generating unique request identifier for each concurrent user request, and return asynchronous acceptance response to client, concurrent user request and unique request identifier are published to message queue;Multiple user requests are batched pulled from message queue, determine request batch, based on each user request in request batch, determine the unique hash digest corresponding to each user, to unique hash digest, carry out query in preset multi-level cache system, determine cache query result;When cache query result is cache miss, request batch is dispatched to GPU computing unit to execute model inference calculation, determine model inference result data, to store model inference calculation result data to multi-level cache system, and it is returned to client by long connection protocol stream.

The application discloses a one-machine performance evaluation method and electronic equipment, and relates to the technical field of computers. The method comprises the following steps: system initialization processing, receiving user initialization parameters, verifying the measured accuracy of at least one application scenario, performing concurrent performance testing to obtain the optimal number of concurrent users when the measured accuracy is greater than or equal to the accuracy threshold, determining the performance index of the large language model all-in-one machine in the current application scenario according to the optimal number of concurrent users, determining the performance index of the large language model all-in-one machine in the current application scenario as zero when the measured accuracy is less than the accuracy threshold, and determining the comprehensive performance index according to the performance indexes in the application scenarios. The application can simultaneously consider factors such as hardware computing power, software scheduling and model accuracy, avoid the one-sidedness of traditional methods that only look at a single index, and thus more intuitively reflect the content generation capability and efficiency of the all-in-one machine in a real application scenario.

The application relates to the field of data processing and discloses a user concurrent access control method and related device, which are used for improving the efficiency of user concurrent access. The method comprises the following steps: obtaining the access authority and priority of a plurality of target users, and performing token distribution on the plurality of target users according to the access authority and priority, so as to obtain the token quantity; obtaining at least one first token according to the token quantity corresponding to each target user, and caching the at least one first token to a preset token bucket, and setting the maximum capacity of the token bucket; when a target user accesses a shared resource, obtaining a target quantity of at least one second token from the token bucket; when the target user completes the access to the shared resource, releasing the at least one second token, and putting the at least one second token back into the token bucket; periodically checking the token quantity in the token bucket, and dynamically adjusting the token quantity and the acquisition rate of the token bucket according to the access state.

The invention provides a multi-platform large model dynamic fragmentation calculation method and system based on computing power self-sensing, and relates to the technical field of computing power resource scheduling. According to the calculation method, due to bandwidth normalization, temperature factors and a complete computing power self-sensing mechanism, stable execution performance can be kept, reasoning delay jitter can be reduced, the computing power prediction capacity of mu ST can actively adjust fragments before the computing power is reduced, passive redeployment is avoided, and re-fragmentation and migration overhead can be reduced; the multi-granularity fragmentation system supports multiple structures, and the deployable range of the model can be effectively improved; a longer reasoning sequence and a higher number of concurrent users can be supported through state-level fragmentation, and the throughput of the long sequence is improved; according to the composite search method combining differentiatable Bandit and GFlowNet, a global sub-optimal even optimal fragmentation strategy can be quickly found in a complex search space, the exploration time can be shortened, and the common local optimum problem of a heuristic method is avoided; the system can be expanded to more than ten cloud-side-end devices for cooperation, and the expansion capability is remarkably improved.