19 results about "Performance guarantee" patented technology

The invention discloses a task scheduling and cache optimization method in a storage and calculation collaborative edge computing network, and aims to optimize the service delay cost of a user and the cache deployment cost of a service provider. The method comprises the following steps: modeling a reusable task scheduling and cache optimization problem in a storage-computing collaborative edge computing network, and decoupling the reusable task scheduling and cache optimization problem into two sub-problems: a task scheduling problem for minimizing service delay cost, and providing a dynamic task scheduling algorithm based on a merging mechanism for the task scheduling problem. The invention provides a calculation result caching algorithm combining dynamic planning and greedy, and further provides a forward-looking pre-caching strategy for solving the problem of minimizing the service caching cost. The task calculation scheduling and result caching method with reusability is provided for space-time correlation of task requests in a storage and calculation collaborative edge calculation network, strict performance guarantee is provided, the method has wide applicability, and the method is suitable for large-scale popularization and application. And challenges of resource limitation and high real-time requirements in a complex calculation scene can be efficiently dealt with.

The invention discloses a resource adjustment method, device and equipment of a system. Firstly, the current state and the next action of a target system can be obtained, the next state is obtained after the action is executed, and default penalty and a multi-dimensional reward signal matrix in the process that the current state is changed to the next state are calculated. And performing nonlinear combination on the reward signal matrix to form a preliminary reward function, and calculating a dynamic discount factor of a next state at the same time. And constructing a total reward function in combination with the default penalty and the preliminary reward function, and iteratively updating the value function based on the reward function and the dynamic discount factor until convergence. And finally, carrying out effective resource adjustment on the target system according to the converged value function. According to the method, flexible default punishment is realized by quantifying the constraint violation degree, the expression ability of multi-dimensional rewards is improved by adopting a nonlinear reward combination, and the dynamic discount factor is introduced to consider short-term and long-term benefits, so that the adaptability, the optimization effect and the continuous performance guarantee of a resource scheduling algorithm are remarkably enhanced.

The invention belongs to the technical field of robot intelligent control and energy management crossing, and particularly relates to a robot servo system self-adaptive energy-saving control method based on a task power spectrum, which comprises the following steps: establishing a task power spectrum model based on multi-modal sensor data fusion, and quantifying robot task dynamic characteristics; establishing a multi-physical field coupling loss model comprising a motor loss model and a power device loss model, cooperatively optimizing the bus voltage and the PWM switching frequency based on the power spectrum model and the loss model, and determining an optimal working point parameter combination; smooth parameter switching is realized by adopting a variable parameter self-adaptive predictive control algorithm; system global energy efficiency optimization and control performance guarantee are realized through a three-layer control architecture comprising a cognitive layer, a decision layer and an execution layer and a four-domain collaborative optimization mechanism in a time domain, a frequency domain, an energy domain and a heat domain. According to the method, the prediction precision under extreme working conditions is improved by adopting multi-physical coupling modeling, the performance degradation of a traditional method is avoided, and the robust performance of the system is improved.

The invention discloses an expressway construction project quality digital detection method and system, and belongs to the field of data processing.The expressway construction project quality digital detection method comprises the following steps that full-life periodic performance data of key parts of project facilities are collected, cleaned, aligned and subjected to feature engineering; the method systematically solves the problems of'heavy short-term qualification and light long-term performance 'in the prior art, and lays a data foundation of long-term evaluation by collecting and processing full-life periodic performance data; a digital twinborn model fusing real-time data is constructed, mechanics and a material degradation algorithm are integrated, dynamic simulation of long-term performance evolution of the structure under the environment and load effect is achieved, a machine learning algorithm is implanted, real-time evaluation of structural damage and prediction of the future performance degradation trend are achieved, and the method is suitable for large-scale popularization and application. Potential risks can be identified and pre-warned at the early stage of operation, so that the quality control is changed from passive acceptance to active performance guarantee throughout the whole life cycle.

The invention provides an edge service deployment and user distribution method based on dobby machine learning, which belongs to the technical field of mobile edge computing, and comprises the following steps: constructing an edge service deployment model and a service delay model; based on resource utilization and service satisfaction, a service utility quantitative representation model is constructed, a service utility maximization-oriented edge service deployment and user allocation joint optimization mathematical model is constructed aiming at user specific constraints in an edge computing environment, and aiming at problem characteristics, it is assumed that each edge server is regarded as an arm. Each user is regarded as an independent player, the problem is converted into a dobby machine problem, the problem is solved based on a dobby machine learning method, development-utilization tradeoff in the dobby machine problem is processed by adopting an upper confidence bound strategy, and an edge service deployment scheme and a user distribution scheme with theoretical performance guarantee are obtained. According to the invention, the overall service effectiveness of the service provider can be maximized.

A node-based performance guarantee compliance system is disclosed, comprising at least one orchestrator and at least one node node comprising at least one storage volume. The orchestrator is configured to allocate storage and application network traffic to and from the node in accordance with a predefined performance guarantee.

The application discloses an element replacement adaptive test optimization method and system, and relates to the technical field of element test optimization. The method comprises the following steps: extracting performance data and element types of scarce elements in target element replacement scene information, performing first-order multidimensional screening, and obtaining a verified rich element combination set; performing virtual characterization reverse fine-tuning, and obtaining a verified fine-tuning rich element combination set; obtaining a verified fine-tuning rich element combination sample set and a sputtering experiment result set; performing test evaluation according to a preset performance test type, and determining a target fine-tuning rich element combination. The application solves the technical problems of low test efficiency, high research and development loss, difficult performance guarantee and insufficient differentiation of rich element replacement scarce element test in the prior art, achieves the replacement test optimization of rich elements on scarce elements, improves the research and development efficiency, reduces the research and development loss, and guarantees the performance and differentiation potential of the rich element combination.

The present application relates to the technical field of administration, in particular to a security personnel intelligent scheduling system and method based on hierarchical architecture. The system adopts five-layer architecture of data management layer, feature calculation layer, intelligent core layer, decision support layer and user interaction layer to realize business logic decoupling. The method core includes: converting requirements into structured portraits through a project analyzer; the intelligent scheduling engine adopts a multi-objective evolutionary algorithm integrating robust optimization, generates a resilient scheduling scheme capable of resisting the worst absence scenario by defining an uncertain set of personnel availability; the dynamic scheduler adopts an online algorithm with a guaranteed competitive ratio to provide real-time decisions with bounded performance for unpredictable temporary tasks. The scheme realizes the change from post-event remediation to pre-event prevention, guarantees business continuity, and provides quantifiable performance guarantees for scheduling decisions in dynamic environments.

The invention relates to the technical field of administrative management, in particular to a security personnel intelligent scheduling system and method based on a layered architecture. The system adopts a five-layer architecture of a data management layer, a feature calculation layer, an intelligent core layer, a decision support layer and a user interaction layer to realize business logic decoupling. The core of the method comprises the following steps: converting a demand into a structured portrait through a project analyzer; the intelligent scheduling engine adopts a multi-objective evolutionary algorithm fused with robust optimization, and generates a flexible scheduling scheme capable of resisting the worst absence scene by defining an uncertain set of personnel availability; and the dynamic scheduler adopts an online algorithm with competition ratio guarantee to provide real-time decisions with bounded performance for unpredictable temporary tasks. According to the scheme, shift arrangement is changed from post-event remedy to pre-event prevention, and quantifiable performance guarantee is provided for scheduling decisions in a dynamic environment while service continuity is guaranteed.

The invention discloses a discrete agent-based load group modeling and consistency regulation and control method and system, and the method comprises the steps: building a discrete time load group model based on a load group, and enabling the discrete time load group model to comprise a leader and a plurality of followers; determining a system matrix including an adjacent matrix and a leader connection matrix; dividing the followers by using competition relationship representation; obtaining a low-gain state feedback matrix; setting the maximum response time of regulation and control; in the regulation and control process, a complete intermittent control protocol and a partial intermittent control protocol are generated; respectively calculating control tracks of followers under different control protocols and corresponding saturation constraint values; calculating a consistency error between the system states of the leader and the follower at the regulation and control time k; and judging whether the regulation process is ended or not according to the consistency error. According to the method, control paradigm innovation, heterogeneous system compatibility, time-varying demand adaptation, communication overhead optimization, stable performance guarantee and system self-evolution can be realized, and the flexibility, high efficiency and engineering practicability of power load regulation and control are remarkably improved.

The application discloses a social media linear event detection method based on graph stream, comprising the following steps: S1, using a graph stream to model social media time, and defining a time window and a time sequence graph; S2, using a stream calculation model based on the time window W, calculating an edge weight value w based on a longest incremental subsequence; S3, adding a relative rising amplitude based on LIS to define the edge weight, that is, the ratio of the total increment value to the first value of the sequence. The method has high applicability, is robust to noise, considers inherent correlation between keywords, and only depends on a text stream with a time stamp; the method has linear worst-case time and space complexity, high applicability and parallelism, and can provide worst performance guarantee for general graph stream-based event detection; the burst event detection based on keywords and co-occurrence behaviors can reduce the negative influence of the "abnormal waves".

The present application relates to the technical field of artificial intelligence computing power scheduling, in particular to a load balancing and performance guarantee method for multi-modal AI computing power service, comprising: firstly, analyzing request characteristics, extracting a computing work set and a minimum safe capacity to generate a local key-value cache baseline, and fitting to generate a minimal algebraic arrival curve of network direct writing traffic; then, combining the baseline, the curve and the network topology routing hop count to build a key-value cache non-eviction model and solve the physical cache capacity limit; further, determining the number of isolated paths according to the limit and the single-path capacity, calling the hardware register to set the capacity bitmask, and building a space-time physical isolation architecture; finally, when the traffic breaks through the upper bound of the curve, establishing an orthogonal damping constraint relationship based on equivalent arithmetic strength, and synchronously reducing the computing end micro-batch and the network end transmission unit. The present application solves the problem of physical squeezing of local cache by network direct writing through bottom-layer physical isolation and double-end orthogonal feedback.

The invention relates to the technical field of H5 application performance testing, and provides a performance testing method and device, computer equipment and a readable storage medium. The performance testing method comprises the steps that in the testing process of an H5 page, basic performance indexes corresponding to the H5 page are collected in real time; monitoring resource loading data of static resources corresponding to the H5 page and incremental data after dynamic routing change; generating performance data according to the basic performance index, the resource loading data and the incremental data; if it is determined that the performance data has a risk according to a preset performance index early warning condition, abnormal early warning information is generated; and sending the abnormal early warning information to a development terminal corresponding to the H5 page to complete the test of the H5 page. According to the method, the blank of performance monitoring in a complex scene in the vertical field in the prior art is effectively filled, and an efficient and reliable performance guarantee scheme is provided for industries such as finance and medical health care which are highly sensitive to user experience.

The invention discloses a service product automatic scheduling method and system. The method comprises the following steps: obtaining multi-dimensional scheduling information of a target work order and candidate service personnel; on the basis of a preset scheduling rule, performing capture-to-score calculation on the target work order and the candidate service personnel, the score calculation being formed by taking a plurality of scheduling rules as factors, configuring a weight for each scheduling rule, and generating a matching score of the work order and the service personnel according to a scoring formula; calling a global optimal matching algorithm in the range of at least one batch or the whole city, and obtaining an optimal matching scheme of the work order and the service personnel according to the matching score; performing scheduling result detection on the optimal matching scheme based on an anomaly detection rule; and if abnormity is detected, performing correction processing on the scheduling result to generate a scheduling result, and if no abnormity exists, taking the optimal matching scheme as the scheduling result. According to the invention, higher accuracy of a housekeeping scheduling result, business consistency and service performance guarantee can be realized.

The invention discloses a performance evaluation method and system for automatic testing equipment of a vehicle machine, and the method comprises the steps: collecting the historical testing data of the automatic testing equipment of the vehicle machine in a preset testing period, constructing an original data sample, and carrying out the data preprocessing of the original data sample, and forming a standardized data sequence; dynamically grouping the standardized data sequence according to the test scene type, each group corresponding to one test scene, and arranging each group of data in a descending order according to a preset performance index; based on the data arranged in the descending order, the performance guarantee rate under each test scene is calculated, and the performance guarantee rate is defined as the probability that the automatic test equipment of the vehicle machine reaches a preset performance threshold value under the specific test scene; and associating the performance indexes and the guarantee rate thresholds in each test scene, analyzing the performance indexes and the guarantee rate thresholds, and outputting a performance evaluation result about the automatic test equipment of the in-vehicle infotainment system. According to the invention, a technician is helped to carry out refined performance optimization and troubleshooting, and the overall integrity and stability of the vehicle-mounted information entertainment system are improved.

The application discloses a resource adjustment method, device and equipment of a system. First, the current state and the next action of the target system can be acquired, the next state is obtained after the action is executed, and the default penalty and the multi-dimensional reward signal matrix in the process of changing from the current state to the next state are calculated. The reward signal matrix is combined to form a preliminary reward function, and the dynamic discount factor of the next state is calculated. The total reward function is constructed by combining the default penalty and the preliminary reward function, the value function is iteratively updated based on the reward function and the dynamic discount factor until convergence. Finally, the target system is effectively adjusted according to the converged value function. The application realizes flexible default penalty by quantifying the constraint violation degree, improves the expression ability of the multi-dimensional reward by adopting nonlinear reward combination, and introduces the dynamic discount factor to consider short-term and long-term benefits, which significantly enhances the adaptability, optimization effect and continuous performance guarantee of the resource scheduling algorithm.

The application discloses a task scheduling and cache optimization method in a storage-computing collaborative edge computing network, so as to optimize the service delay cost of a user and the cache deployment cost of a service provider. A reusable task scheduling and cache optimization problem in the storage-computing collaborative edge computing network is modeled, and the problem is decoupled into two sub-problems: a task scheduling problem for minimizing the service delay cost, and a dynamic task scheduling algorithm based on a merging mechanism is proposed for the task scheduling problem. A calculation result cache algorithm combining dynamic programming and greediness is proposed for a service cache cost minimization problem, and a forward-looking pre-cache strategy is further proposed. The application faces the space-time correlation of task requests in the storage-computing collaborative edge computing network, and proposes a task calculation scheduling and result cache method for tasks with reusability. The method not only provides strict performance guarantee, but also has wide applicability, and can efficiently cope with the challenges of resource limitation and high real-time requirement in a complex computing scene.

The application discloses a kind of highway construction engineering quality digitization detection method and system, belong to data processing field, this highway construction engineering quality digitization detection method includes following steps: the full life cycle performance data of key position of engineering facility is collected and is washed, alignment and feature engineering, the problem of prior art "heavy short-term qualified, light long-term performance" is systematically solved, by collecting and processing full life cycle performance data, long-term evaluation data foundation is laid;Build digital twin model fusing real-time data, and integrate mechanics and material degradation algorithm, realize the dynamic simulation of long-term performance evolution of structure under the action of environment and load, implant machine learning algorithm, realize real-time evaluation of structural damage and prediction of future performance degradation trend, so that potential risks can be identified and warned in early operation, so as to change quality control from passive acceptance to active performance guarantee throughout the life cycle.

The invention provides a computing task unloading method based on space-ground cross-domain multi-slice computing resource management. The computing task unloading method comprises the steps that a ground MEC system comprises a plurality of MEC areas, and each MEC area is provided with at least one server for providing computing services; constructing a ground time delay model, an inter-satellite routing time delay model and a total time delay model; constructing a slice isolation degree evaluation model according to a duration ratio capable of guaranteeing calculation of slice isolation performance indexes in the total observation time; constructing a target function according to the average resource utilization rate, the average resource reuse degree and the user side performance guarantee rate of the ground MEC system within the total observation time; obtaining the time delay of unloading the calculation task to each server through a ground time delay model and a total time delay model, and constructing a constraint condition of a target function in combination with a time delay requirement of the calculation task; and solving the objective function, and storing the unloading decision of each calculation task in the MEC region when the objective function value is maximum as a final calculation task unloading decision.