57 results about "Service allocation" patented technology

The invention provides a truck-unmanned aerial vehicle cooperative dynamic scheduling method and system in emergency logistics, and relates to the technical field of unmanned aerial vehicle intelligent scheduling. Constructing a truck-unmanned aerial vehicle cooperative distribution network, wherein each truck is equipped with a cooperative unit comprising a large unmanned aerial vehicle and a small unmanned aerial vehicle; the network comprises warehouses, hub points and demand points; establishing a mixed integer programming model by taking minimization of the total operation cost as a target and taking electric quantity management, service distribution, a time window and collaborative feasibility as constraints; and solving the model by adopting a randomized greedy algorithm, and synchronously deciding a truck path and an unmanned aerial vehicle task in single iteration to obtain a truck path scheme, an unmanned aerial vehicle service distribution scheme and a dynamic electric quantity scheduling scheme. Therefore, the cost optimization and dynamic coordination of emergency logistics scheduling are realized, and the efficiency and feasibility of emergency distribution are effectively improved.

A policy determining or resource allocation method includes obtaining, by a policy control network element and a computing service request from a server. The computing service request includes computing service description information of a target computing service of a terminal device, and the computing service request is used for requesting allocation of computing power resources for the target computing service; and determining, by the policy control network element, a target QoS policy for the target computing service based on the computing service description information. The target QoS policy includes a computing power QoS policy.

The embodiment of the invention provides a communication method and device based on an MCP protocol, a storage medium and a program product. The method comprises the following steps: acquiring publisher information of the MCP service; distributing a unique identifier for the MCP service according to the publisher information; combining the unique identifier with a tool identifier of an MCP tool provided by the MCP service to obtain a combined tool identifier; based on the combined tool identifier, adding an MCP tool in a tool list; wherein the tool list is used for recording the MCP tool which can be called by the first pre-training language model.

A method includes, using a mobile device connected to an industrial network of an industrial system, receiving a chainable compute service assignment from a first intelligent industrial device of the industrial system that assigns a chainable compute service to the mobile device or assignment from a cloud-based device or system connected to the industrial network that assigns the chainable compute service to the mobile device; and using the mobile device, performing the chainable compute service.

A system and method is presented that extracts snippets form web pages according to specially designed logic. The extracted snippets might be made relevant to, i.e., indexed by, a location and time / day applicability. Such snippets may be thought of as apps or services that are defined only when a mobile terminal is in a pre-defined geographical area at a certain time and day (e.g., as defined by a calendar of events). Extracted snippets are stored and made searchable. Methods and a system are described to control the display of snippet search results. Snippets may be selected by user or by programmed logic and executed on the mobile terminal or in remote servers without the need to download the app or source code associated with the snippet.

This application belongs to the field of artificial intelligence and relates to a service provider allocation method, including: determining whether a service allocation request has been received; if so, parsing target service scenario information from the service allocation request; obtaining a target decision network corresponding to the target service scenario information; receiving a policy expectation value, input parameter values ​​corresponding to condition factors, and service provider parameters corresponding to the service provider; solving the policy on the target decision network based on the input parameter values ​​to obtain the optimal solution of the target policy state node corresponding to the policy expectation value; determining the target service provider based on the optimal solution and the service provider parameters, and allocating the target service provider to the target service scenario corresponding to the target service scenario information. This application also provides a service provider allocation device, computer equipment, and storage medium. Furthermore, this application relates to blockchain technology, and the target decision network can be stored in the blockchain. This application improves the processing efficiency and accuracy of service provider allocation.

The application discloses a network spectrum fragmentation minimization routing resource allocation method and device, the method comprises two stages of path selection and spectrum allocation, the path selection stage takes maximizing path resource utilization as the target, obtains optical network topology information, filters the optimal path through quantifying spectrum resource availability and concentration degree of the link and the path, and forms a candidate path set; the spectrum allocation stage takes minimizing spectrum fragmentation generation and reducing service blocking rate as the target, converts the IP service into optical layer frequency gap demand, filters the continuous idle spectrum block meeting the spectrum constraint condition in the candidate path set to form a frequency block candidate set, determines the optimal frequency block through quantifying the close degree of the frequency block and the occupied resource and the influence degree of the frequency block deployment on the link resource, completes service allocation, and updates the link frequency gap use state in real time after the allocation. The application effectively reduces spectrum fragmentation, improves spectrum resource utilization and network transmission reliability, and adapts to high dynamic and high burst service demand.

The invention discloses a customer service allocation method and device, equipment, a medium and a program product, and belongs to the field of customer service allocation. The method comprises the following steps: acquiring a consultation question of a service object and respective working state information of a plurality of candidate customer services; performing classification operation on the consultation questions through a first artificial intelligence model to obtain a first question category; screening out a first number of candidate customer services carrying a first question category label from the plurality of candidate customer services, wherein the first question category label corresponds to the first question category; based on the respective working state information of the plurality of candidate customer service staff, screening out a second number of candidate customer service staff of which the working states meet the working state condition from the plurality of candidate customer service staff; and based on the intersection of the first number of candidate customer service staff and the second number of candidate customer service staff, determining the customer service staff for processing the consultation question. According to the method, question classification is carried out through the first artificial intelligence model, and compared with keyword matching of related technologies, the classification result is more accurate.

An example computer-implemented method includes accessing service request data indicative of a service request, the service request having a service type and one or more service parameters. The method includes computing a complexity score associated with the service request based on the service type and the one or more service parameters. The method includes selecting a first courier of a plurality of candidate couriers based on the complexity score associated with the service request. The method includes outputting first instructions to a first courier device associated with the first courier. The first instructions are executable by the first courier device to cause a service assignment to be provided for display via a user interface of the first courier device, the service assignment indicating the first courier is to perform the service request.

The application discloses a service deployment method and device and electronic equipment, wherein the method comprises the following steps: receiving an access request of a user, and dispatching the access request to a to-be-deployed service via routing; determining a video memory requirement of the to-be-deployed service based on the access request, and generating a configuration file based on the video memory requirement and a graphics card located on a server; allocating video memory for the to-be-deployed service according to the configuration file, deploying an instance in the video memory through the to-be-deployed service, wherein the video memory is located in a target graphics card of a target server, the target server is a server used for deploying the to-be-deployed service, and the target graphics card is a graphics card in the target server which provides video memory resources for the to-be-deployed service; and allocating the access request to the deployed instance and running the instance, so as to deploy the to-be-deployed service to the target server. The application automatically allocates the video memory in the target graphics card of the target server for the to-be-deployed service through the configuration file, realizes the automatic deployment of the service, and does not need to deploy the service to the target server by manpower.

The application provides a large-scale optical network resource allocation method based on iterative learning, comprising: initializing an optical network topology and a state of spectrum resources of each link; initializing a node feature code of each node and a link feature code of each link; dynamically updating v i , e j , and a current service request according to a current network state, and simultaneously generating an input state S I of a corresponding Agent; the input state S I is sent into the Agent as a basis for decision-making; a feasible solution conforming to an optical path constraint is gradually constructed; the decision-making is reinforced; a reward value R of an action is calculated; the updated reward value R is used for further optimization of the decision-making of the Agent; an EGAT model is trained and optimized; the EGAT model is evaluated and simulated; and a service allocation strategy is gradually constructed in combination with iterative learning, which can effectively cope with large-scale network topology changes and significantly improve the global performance and efficiency of scheduling.

This invention discloses a method and system for scheduling and distributing image streams based on a distributed cascaded power grid. The method includes: determining whether an analysis task should be issued based on device affiliation and scheduling strategies, merging issued tasks to generate sub-tasks; when a user selects to prioritize querying an automatic acquisition task of the cyclic frame extraction library type, retrieving frame images that meet the conditions from the cyclic frame extraction library cache; when an analysis task is executed on a lower-level platform, selecting an analysis service cluster based on the parent platform and task type, allocating services according to the current load, and completing the task; subsequently, sending the results back to the parent platform; when an analysis task is executed on the parent platform, selecting an appropriate analysis service cluster based on the business system and task type, allocating services according to the current load, and completing the task. This invention improves upon existing solutions that suffer from queuing congestion caused by cross-network bandwidth and concurrency bottlenecks, and low stability of critical services under complex cross-network conditions.

The application provides a truck-UAV collaborative dynamic scheduling method and system in emergency logistics, and relates to the technical field of UAV intelligent scheduling. A truck-UAV collaborative distribution network is constructed, each truck is equipped with a collaborative unit containing a large UAV and a small UAV; the network contains warehouses, hub points and demand points; a mixed integer programming model is established with the minimum total operating cost as the target, and the power management, service allocation, time window and collaborative feasibility as the constraints; a randomized greedy algorithm is used to solve the model, and the truck path and UAV task are decided synchronously in a single iteration to obtain the truck path scheme, UAV service allocation scheme and dynamic power scheduling scheme. Thus, the cost optimization and dynamic collaboration of emergency logistics scheduling are realized, and the efficiency and feasibility of emergency distribution are effectively improved.

The embodiment of the invention provides a service scheduling method and device for a cross-domain computing power network, equipment and a storage medium, and relates to the technical field of network communication. The method comprises the following steps: splitting a service request into sub-services, generating a service unloading constraint set and a link resource constraint set, generating a target function according to node resource cost and total delay corresponding to the sub-services allocated to physical nodes, forming an optimization problem according to the service unloading constraint set, the link resource constraint set and the target function, and for each sub-service, generating a link resource constraint set according to the optimization problem. And determining an initial computational domain based on user position information corresponding to the service request, solving an optimization problem in the computational domain to obtain the allocated physical nodes corresponding to the sub-services, otherwise, selecting a new computational domain from the corresponding hierarchical set for solving until the allocated physical nodes corresponding to all the sub-services are obtained. And by adopting a strategy of combining sub-service splitting with dynamic selection of the computational domain, the risk of information leakage is reduced, and meanwhile, the service scheduling efficiency of the cross-domain computing power network is improved.

This application discloses a method, apparatus, device, and readable storage medium for generating a database cloud service. The method involves acquiring a user-input database cloud service generation instruction, which includes configuration parameters for the target database cloud service to be generated. Based on these parameters, storage space resources and network resources are allocated to the target database cloud service. A container is started based on a pre-built database image, and the container is deployed to the storage space and network resources. CPU and memory resources are further allocated to the container, and the container is run to generate the target database cloud service. Because this application's solution generates the database cloud service by building a cloud computing platform and deploying the database cloud service in a container, the underlying physical resources are isolated, ensuring that resources between different containers do not interfere with each other. By using Docker containers to achieve physical resource allocation and isolation for the database cloud service, the security of the database cloud service is improved, and user data information is protected.

A method for assigning a set of services to a set of data links between a mobile device and at least one station, comprising a selection step (S1) of a subset of data links, including a substep (S11) of determining performance parameters for each data link, a substep (S12) of converting these performance parameters into objective values, and a substep (S13) of selecting said data links based on said objective values; a scheduling step (S2) of the data links based on at least one scheduling criterion; and an assignment step (S3) comprising assigning the services based on a service schedule and the data link schedule. Figure for the abstract: Fig. 2

This application relates to a session management method, apparatus, computer device, and computer-readable storage medium. It includes: receiving a login request from a first front-end service, carrying a service identifier header; the first front-end service running in a browser, and the browser running at least one front-end service; querying the corresponding cookie name in a configuration center based on the service identifier header; creating a corresponding session based on the cookie name; generating response information based on the cookie name and sending it back to the browser. This method assigns different cookie names to front-end services running in the same browser, allowing users to access the same back-end service through multiple front-end services in the same browser without exiting and creating a new session, seamlessly switching between different identities, improving user experience and operational efficiency; by assigning a session cookie name through the service identifier header of each front-end service, it can resolve session conflicts between multiple front-end services on the same browser.

In at least one embodiment, processing can include: assigning services a non-critical polling priority or a critical polling priority, where each service is associated with a queue set including a completion queue (CQ) and receiving queue (RQ) associated with received messages stored in memory of the local node and sent by a remote node via remote direct memory access (RDMA); partitioning CQs of the queue sets in accordance with assigned polling priorities to generate a non-critical CQ list and a critical CQ list; polling the non-critical CQ list by a non-critical poller at a non-critical polling frequency for completion signals or indicators associated with received non-critical messages of the local node to be serviced; and polling the critical CQ list by a critical poller at a critical polling frequency for completion signals or indicators associated with received critical messages of the local node to be serviced.

The application provides a method for distributing a client to access a low-delay server based on a master service, comprising the following steps: the client acquires a local feature code and sends login account information to a master server; the master server checks the login information; the master server acquires regional information and telecommunication network information of the client according to the ip information of the client, and acquires service server information closest to the client; two service server node information are selected, and the login information and the feature code of the client are synchronized to the two service servers; the master server distributes service server address information to the client and returns token data and data encryption keys to the client; the client selects a service server to connect; and the client performs service data interaction through the token data and the data encryption keys. The application has the beneficial effects that the logical decoupling of system login and service data interaction is realized, and the possibility that a background service system can be deployed across regions or different telecommunication networks is realized.

Various examples are directed to a service assignment system for providing transportation services. The service assignment system may receive a transportation service request from a user. The transportation service request may describe a transportation service having a service start location and a service end location. The service assignment system may generate a plurality of routes for executing the transportation service. The service assignment system may send proposed route data describing at least a portion of the plurality of routes to a first autonomous vehicle (AV). The service assignment system may receive, from the first AV, route data describing a first route to execute the transportation service and send, to the first AV, instruction data instructing the first AV to begin executing the transportation service.

The invention relates to the field of intelligent allocation, and discloses a customer service allocation method and equipment based on a large language model, and a storage medium. The method comprises the following steps: receiving online question data; performing configuration analysis on the online question data to obtain a configuration path; when the configuration is manual configuration, carrying out seat allocation on the online question data to obtain an allocated seat number, and sending the allocated seat number to an address corresponding to the allocated seat number; when the configuration is intelligent configuration, performing knowledge retrieval on the online question data to obtain a retrieval result; when the retrieval result is not null, reply arrangement is conducted on the retrieval result according to a large language model, and a reply result is generated and transmitted to the question address; if yes, performing seat conversion on the online question data to obtain a converted seat number, and sending the converted seat number to the question address; and adding the question-answer data into the question-answer knowledge base to obtain a new question-answer knowledge base. In the embodiment of the invention, the accuracy of identifying the client intention and matching the professional customer service is improved by utilizing the large language model and the plug-in knowledge base.

A method includes controlling services for a first device in a first group based on a first service allocation for the first group during a first portion of an interval, controlling services for a second device in a second group based on a second service allocation for the second group during the first portion, determining a first individual usage metric for the first device, determining a first group usage metric for the first group, transferring the first device from the first group to the second group responsive to the first group usage metric exceeding the first service allocation, and controlling services for the first device in the second group based on the second service allocation during a second portion of the interval.

Embodiments of the present application relate to the technical field of terminals, and provide a Bluetooth connection processing method and an electronic device. The method comprises: a first device receiving a first connection request sent by a second device, the first connection request including a first port number historically assigned by the first device for a first service; in response to the first connection request, the first device establishing a first Bluetooth link with the second device; when a port number corresponding to the first Bluetooth link is the first port number, and a port number currently assigned by the first device for the first service is a second port number, and upon receiving a first message sent by the second device, a message format of the first message being a format corresponding to the first service, the first device disconnecting the first Bluetooth link; and after disconnecting the first Bluetooth link, the first device establishing, on the basis of a third port number currently assigned by the second device for the first service, a second Bluetooth link corresponding to the first service with the second device. In this way, a Bluetooth link for transmitting data of the first service can be effectively established.

The application provides a new electric vehicle charging load balancing scheduling method, which collects load data and user demand information in real time through an intelligent sensor network, constructs a comprehensive data set and generates real-time state mapping data, analyzes peak overload and trough idle trends using a prediction model to determine load distribution prediction results; based on a two-way communication mechanism, user charging preferences are obtained and charging suggestions are pushed to generate a preliminary resource allocation scheme, genetic algorithm is applied to optimize power distribution, minimize overload risk and maximize resource utilization; through virtual simulation test, load distribution stability is evaluated and the scheme is iteratively optimized; real-time monitoring of load fluctuations, dynamic updating of operating parameters and issuance of control instructions, triggering of standby scheduling mechanism according to user feedback, continuous optimization of service allocation. The application realizes intelligent management of electric vehicle charging load, effectively balances power grid resource allocation, and improves user satisfaction and charging efficiency.

This invention discloses a method and apparatus for joint control of queue scheduling and congestion threshold in data center networks, relating to the field of communication technology. The method includes: the transmitting end distinguishing and marking traffic generated during large model training and mapping it to different queues by a switch; a weight controller selecting a weight template based on bandwidth utilization and congestion information; an ECN controller switching the ECN threshold template based on bandwidth share, transmitted byte increment, and average queue length; a PFC controller generating PFC risks based on shared buffer status and queue buffer usage; and when a PFC risk is detected, the weight controller and ECN controller respectively perform emergency weight template switching and more aggressive ECN threshold template switching. This invention can balance queue bandwidth allocation, reduce queue backlog and PFC trigger probability, and achieve joint regulation of queue service allocation and congestion feedback.

A cybersecurity service assesses, scores, and / or prioritizes activities associated with a directory service. When the directory service is requested to change a directory service assignment, the directory service may first request a verdict from the cybersecurity service. The cybersecurity service may use profiling and / or machine learning to predict directory service assignments. The cybersecurity service may then score and prioritize requests to change / update directory service assignments. Small deviations from predicted directory service assignments, for example, may indicate harmless / normal directory service activity. Larger deviations, though, may indicate abnormal directory service activity. Larger deviations may even indicate malicious directory service activity, such as permission escalation and cyberbreaches. Scoring and prioritization allows for resource allocation and timely mitigations by human experts.

The invention discloses an Internet of Things equipment multi-dimensional intelligent service scheduling method and system, and the method comprises the following steps: S1, request receiving and feature extraction: receiving a service scheduling request, and extracting scheduling feature information from the request; and S2, multi-dimensional scheduling rule matching: according to a preset priority sequence of scheduling feature information, carrying out matching query on the information in a multi-dimensional scheduling rule base in sequence, and once matching succeeds in a certain dimension, terminating a matching process and entering a service distribution stage. The method has the advantage of accurate and efficient scheduling, and solves the problems that in the service scheduling process of existing Internet of Things equipment, accurate and efficient scheduling of various different Internet of Things equipment is inconvenient, and scheduling faults and inconsistency are easily caused.

The invention discloses a quick data storage method based on MySQL sub-library sub-table, and relates to the technical field of data storage. The method is designed for two scenes of strong correlation and weak correlation of the primary key and the service. In the scene 1, the primary key is generated by splicing a user identifier, a calculation task ID and an execution timestamp, taking the first 10-bit hexadecimal number through SHA-256 Hash and converting the first 10-bit hexadecimal number into a decimal system. Aggregating the data to a sub-table through a sub-library and sub-table routing rule, and splitting to generate sub-batches; 32-thread parallel insertion is adopted, transaction atomicity control and primary key continuous optimization gap lock range are combined, and the storage efficiency is improved. And in the scene 2, the major key distributes continuous intervals by the global major key service, and the distributed intervals are recorded through Redis to realize high-availability takeover. Batch SQL + transaction execution is adopted in the two scenes, abnormal retry, bottom writing and primary key conflict processing mechanisms are matched, data consistency and high availability of the system are guaranteed, and data storage performance in the high-concurrency scene is improved.