745 results about "Web transport" patented technology

The invention relates to the technical field of cloud side end computing, and discloses a cloud side end cooperative computing resource dynamic allocation method based on task-aware migration. The method comprises the following steps: acquiring real-time load characteristics and resource demand characteristics of calculation tasks in a cloud side end system, and dividing task priority queues in combination with task type identifiers; extracting historical execution records of tasks at cloud, edges and terminal nodes, constructing a task execution feature library, and generating a resource demand prediction model in combination with real-time load features; analyzing network transmission time delay characteristics of a cloud end and edge nodes, measuring real-time calculation capability fluctuation data of terminal equipment, and establishing an inter-node resource collaboration degree evaluation matrix; generating an initial migration strategy according to the prediction model and the evaluation matrix, monitoring actual resource occupancy deviation of the task, forming a final decision in combination with a node resource state correction strategy, triggering cross-node migration, and synchronously updating the priority queue and the evaluation matrix.

The invention provides a resource scheduling control method and system for a big data server, and the method comprises the steps: constructing a multi-dimensional resource portrait module, collecting the CPU, memory, network, storage I / O load and task queue length of each node in real time, and predicting a resource demand trend through a time sequence algorithm; extracting characteristics such as calculation intensity, data dependence, memory requirements, network transmission quantity and the like; adjusting the weight coefficients of the resource utilization rate, the task completion time and the energy consumption efficiency according to the system load and the historical effect; establishing a bipartite graph model by taking a resource trend as a node feature and a task vector as an edge feature, and calculating a matching score through graph convolution and a multi-objective optimization function; the scheduling scheme is synchronized by adopting a consistency algorithm; automatic rollback and reallocation are carried out when resources are detected to be insufficient; and optimizing a weight coefficient and a network parameter through reinforcement learning. Through the method, the system resource utilization rate can be improved, the task execution efficiency is improved, the overall scheduling effect stability is improved, and the system fault recovery time is shortened.

The invention relates to the technical field of audio and video emergency transmission, and discloses an audio and video low-delay return method and system in an extreme environment. The method comprises the following steps: acquiring original multi-modal data of audio and video acquisition equipment in a target area, and analyzing a data state of the original multi-modal data; and meanwhile, available network transmission links are monitored, and the quality is evaluated. Self-adaptive coding parameters are generated in combination with the link quality and the data state, dynamic coding is executed on original data, and a coding stream suitable for redundant transmission is formed. And carrying out cooperative distribution transmission based on the network link set and the coded stream to generate return data. According to the generation process, a device and energy management instruction is formed and issued to the acquisition and relay device. According to the method, the network state and the content characteristics are optimized in a dynamic coding link in a collaborative manner, and the audio and video quality, the real-time performance and the system energy efficiency which are transmitted back in an extreme environment are improved through a feedback closed loop for transmitting a result to equipment management.

The invention discloses an explosion-proof and intrinsic safety type combined feeder switch state monitoring method based on big data, and relates to the technical field of industrial electrical equipment state monitoring and fault diagnosis, and the method is realized based on a three-level architecture constructed by an edge computing node, a region computing node and a cloud platform. Comprising the following steps: S1, collecting multi-source sensing data of a feeder switch in real time by an edge computing node, and performing feature extraction and fusion calculation on the multi-source sensing data; according to the method for monitoring the state of the explosion-proof and intrinsic safety type combined feeder switch based on the big data, the contradiction between the real-time performance and the accuracy in multi-source heterogeneous data fusion processing is effectively solved, abnormity can be found in the first time, early warning can be triggered, and the reliability of a diagnosis conclusion is improved; and the accuracy and foresight of fault diagnosis are ensured. According to the grading processing mechanism, computing resources are reasonably distributed, the network transmission load is greatly reduced, and the system can stably operate in a complex industrial environment.

The invention relates to a multi-dimensional aging test data analysis system and method, and aims to realize real-time acquisition and intelligent analysis of multiple performance indexes in the aging process of electronic products. The system comprises an information acquisition module, a test scheduling module, a data processing module, an analysis module, an abnormity judgment module, a report module and a communication module. Cooperative work among the modules is realized based on task driving and data circulation, accurate association of test data is realized through bar code binding, and unified analysis is performed in combination with multi-source information such as USB read-write performance, network transmission state and display resolution. The system realizes multi-task concurrent acquisition through a resource-aware scheduling strategy, and the analysis module identifies performance abnormity and outputs a structured report by combining preprocessing, feature extraction and time sequence prediction. According to the method, the test automation level and the anomaly recognition accuracy are improved.

The invention discloses an immersive interactive system and method integrating pet robot perception and AR rendering, and the system carries out the visual-inertial combined mapping and anchor point generation, the coding and network transmission of visual frames and spatial data, the synchronous decoding and coordinate system alignment of a terminal side, virtual object anchoring, and spatial mapping and AR rendering through a robot side. User intention analysis, control issuing and robot control, and low-delay synchronization, timeline alignment and closed-loop consistent maintenance are carried out; according to the method, the first visual angle image collected by the front camera of the pet robot can be utilized, the augmented reality technology is combined, and the user is substituted into the visual angle of the robot, so that the user can'personally feel 'the observation and action process of the pet robot, and the immersion and immediacy of human-pet interaction are remarkably enhanced; and human-machine-virtual object ternary space interaction is realized.

The invention relates to the technical field of audio and video processing, and provides an intelligent card pause prevention optimization method and system for audio and video playing. According to the method, firstly, a playing state data set is collected in real time, and the playing state data set comprises code stream parameters, hardware resource occupation data and network transmission state parameters; then, constructing a play load association graph based on the data set, and describing a mutual influence relationship among parameters; then, generating a dynamic resource allocation strategy according to the play load association map, and adjusting a hardware resource allocation proportion and a network transmission priority; and finally, executing the strategy, continuously monitoring the data change, and dynamically adjusting the strategy to maintain the playing fluency. Therefore, through multi-parameter correlation modeling and dynamic optimization, accurate prevention of lagging is realized, and the audio and video playing experience is improved.

The invention relates to the technical field of data communication, and discloses an intelligent agent high-speed bus implementation method and system based on an FPGA and a dynamic smoothing technology. The method comprises the following steps: constructing a single handshake message through a lightweight protocol, adjusting network indexes by adopting an exponential smoothing method, constructing a pipeline processing unit in an FPGA card by utilizing a VHDL, realizing key updating and encryption processing, constructing a three-layer adaptive structure connection subsystem, and optimizing algorithm parameters and resource allocation according to a running state. And a high-performance bus communication system is formed. On the premise of ensuring the communication security and reliability, the network transmission delay is remarkably reduced, and the data throughput is improved, so that the communication system can meet the requirements of emergency linkage and large data volume transmission in a scene (such as a rail transit station-level system) with a high real-time requirement.

The attack vectors for some denial-of-service cyber attacks on the Internet's Domain Name System (DNS) are bad, bogus, or unregistered domain name DNS requests to resolve domain names that are not registered in the DNS. Some other cyber attacks steal sensitive data by encoding the data in bogus domain names, or domain names otherwise not registered in the DNS, that are transferred across networks in bogus DNS requests. A DNS gatekeeper may filter in-transit packets containing DNS requests and may efficiently determine if a request's domain name is registered in the DNS. When the domain name is not registered in the DNS, the DNS gatekeeper may take one of a plurality of protective actions. The DNS gatekeeper drops requests determined not to be legitimate, which may prevent an attack.

The invention provides a VR game data synchronous transmission method based on a 5G network, and the method comprises the steps: obtaining a multi-type data stream generated during the operation of a VR game, extracting scene rendering data and player interaction data from the multi-type data stream, separating a feature value of each data type, and obtaining a data priority sequence; analyzing the real-time requirements of the scene rendering data and the interaction data according to the data priority sequence, and judging a key data packet which needs to be transmitted immediately; the method comprises the following steps: monitoring a current bandwidth fluctuation condition through a network transmission layer, calculating available bandwidth and delay parameters from network state data acquired in real time, and obtaining a resource allocation reference value in a dynamic scene; and for high-priority data packets, a dynamic resource allocation algorithm is adopted to adjust a transmission queue sequence, a resource allocation reference value is corrected through a bandwidth fluctuation parameter, and a transmission time slot allocation scheme of the key data packets is determined.

The invention provides a coal stockpiling method based on thermal power intelligent coal transportation, which comprises the following steps that: coal storage yard acquisition equipment acquires three-dimensional point cloud, surface texture, space coordinates, material identity and stacker-reclaimer attitude data of a coal pile, and transmits the data to an edge server through an optical fiber wireless redundant network; preprocessing the data to generate a coal seam three-dimensional digital twinborn model containing a spatial position, a component label and stacking time, and supporting virtual roaming; basic information and constraint conditions are input, a stacking plan is generated based on an optimization algorithm, and an operation instruction is generated after verification; the stacker-reclaimer receives the instruction, completes stacking according to track planning through the PLC control system and records data; the digital twin platform monitors the process, automatically alarms when abnormity occurs, updates the inventory in combination with an inventory making algorithm, and generates a report; the stacking effect is evaluated every day, algorithm parameters of the next round are optimized, and closed-loop management is formed. According to the method, the intelligence and accuracy of coal stacking are improved, and efficient operation of the thermal power coal conveying system is guaranteed.

The invention provides a routing control method, which is applied to network equipment with multi-link access capability, and comprises the following steps: carrying out service identification on a to-be-forwarded data flow of the network equipment to obtain service type information of the data flow; obtaining evaluation indexes of a plurality of candidate links of the network equipment; evaluating the plurality of candidate links based on the evaluation index and the service type information to obtain a comprehensive quality score; selecting a target link from the plurality of candidate links according to the service type information, the evaluation index and the comprehensive quality score; and controlling the network equipment to transmit the data flow through the target link. The invention further provides a multi-service parallel routing method, electronic equipment, a computer readable medium and a computer program product. According to the invention, differentiated routing control of multiple service types is realized, quality fluctuation caused by switching of operators is reduced, and the stability and the intelligent level of network transmission are remarkably improved.

The invention discloses a video transmission and grading early warning method based on 5G and Wi-Fi hybrid networking, and relates to the technical field of network transmission and safety monitoring, and the method comprises the steps: firstly deploying fusion anchor points containing three types of core hardware modules, and determining the number of the fusion anchor points; extracting service time delay and bandwidth demand grades in an XR scene, establishing a QoS parameter mapping relation between 5G and Wi-Fi, and reading key parameters through a fusion anchor point to dynamically allocate bandwidths; based on the parameter matrix and the weight matrix, determining a sampling interval and marking a sampling frame; and finally, evaluating a sampling frame threat parameter and executing hierarchical response. According to the invention, while the collaboration of hybrid networking is improved, the accuracy of threat assessment is improved, and the continuity and security of video transmission in an XR scene are ensured.

The embodiment of the invention provides a tag data processing method, RFID middleware and a storage medium. The method comprises the following steps: receiving and caching tag data of a plurality of tags; compressing the label data according to a predetermined compression mode to obtain compressed data; wherein the compression mode is determined according to a data compression level and a label inventory rate; and sending the compressed data. According to the embodiment of the invention, the data processing efficiency is improved, the equipment resource occupancy rate, the data traffic and the bandwidth occupancy of network transmission of middleware at a high inventory rate are greatly reduced, and meanwhile, the mass data processing pressure of an upper platform is reduced. According to the embodiment of the invention, the platform side can receive total label data, and algorithm application development is facilitated. In addition, according to the embodiment of the invention, the packet number and the data compression level are adjusted according to different service requirements, and the method is suitable for service scene requirements with different data volume and time delay sensitivity.

Some embodiments provide a method of executing a distributed application with multiple EPUs that perform computations for the distributed application. The method receives, at a set of one or more scheduling servers, API commands expressed in a first programming layer and related to computations assigned to a set of EPUs and a set of forwarding criteria specifying a manner for forwarding results of the assigned computations among the EPUs in the set. The method generates, from the API commands, a set of network configuration data expressed in a second networking layer that is for configuring forwarding elements of a network to forward the results according to the specified set of forwarding criteria. The generation includes translating programming layer identifiers of EPUs and forwarding operations to networking layer identifiers needed to forward the results to destinations in the network. The method distributes the generated configuration data to multiple forwarding elements that form a network to configure the forwarding elements.

The invention relates to a digital twin-driven distributed warehousing system and method, and belongs to the technical field of intelligent logistics. The system comprises a sensing execution layer, a network transmission layer, an edge computing layer, a cloud platform layer and an application service layer. The method comprises the following steps: acquiring storage physical entity data through a perception execution layer; the data is transmitted to the edge computing layer and the cloud platform layer through the network transmission layer; in the cloud platform layer, a high-fidelity virtual warehouse is constructed and synchronized through a digital twin engine; using a multi-agent reinforcement learning algorithm to perform centralized training in a digital twin environment to generate a distributed cooperative scheduling strategy; and issuing the strategy to an edge computing layer and a sensing execution layer, and driving an autonomous mobile robot cluster to execute a cooperative task. According to the invention, step-type improvement of the warehousing system in flexibility, intelligence and cooperative capability is realized, and the problems of rigid bottleneck, non-optimal decision and low cooperative efficiency of a traditional system are solved.

The invention provides a Web page first screen loading acceleration method and system, a medium and equipment, and relates to the technical field of Web front-end performance optimization and network transmission, the method comprises the following steps: after obtaining a request of a user for accessing a URL (Uniform Resource Locator), analyzing an HTML (Hypertext Markup Language) and constructing a DOM (Document Object Model) tree; marking first screen resources to obtain a first screen resource list; key resources are inserted into the head of the loading queue, and non-key resources are marked as defer; if the weak network is detected, degrading the picture quality; after the CSSOM is ready, text and layout are rendered immediately, and placeholders are replaced after pictures are asynchronously loaded; when the delay is high, switching to an edge CDN node or starting a QUIC protocol; and pre-fetching resources are predicted based on user behaviors, and the pre-fetching resources are stored in a Service Worker cache. According to the method, the first screen loading time can be shortened, the maximum content drawing time is shortened, the network transmission cost is saved, and the cache utilization efficiency is improved.

The invention relates to the technical field of video monitoring, and provides an intelligent code rate control method for the field of indoor video monitoring, which comprises the following steps: S1, a camera continuously collects video streams of an indoor monitoring scene and pushes the video streams to a streaming media server; s2, decoding the received video stream data to obtain YUV format data, preprocessing the YUV format data, inputting the preprocessed YUV format data into a personnel dynamic detection model based on a deep learning algorithm, and identifying and outputting the motion state of indoor personnel; s3, a constant code rate factor CRF value of an encoder is adjusted in real time based on the personnel dynamic detection result, a low CRF value is adopted in a static scene to reduce the code rate, and the CRF value is adjusted in a graded mode according to the personnel number and the motion intense degree in a dynamic scene to improve the code rate; s4, writing the latest calculated constant code rate factor CRF value into an encoder, and performing intelligent decoding on the video stream data; and S5, carrying out storage or network transmission. And dynamically updating the constant code rate factor CRF value of the encoder according to the model detection result, thereby achieving the effect of balancing the code rate and the image quality.

The invention relates to an intelligent ship water diversion method and system based on RTK and inertial navigation fusion, and the method comprises the steps: firstly, deploying and calibrating an RTK base station at a wharf commanding height, generating a differential correction in real time, and broadcasting the differential correction to a shipborne end; utilizing RTK surveying and mapping equipment to collect shoreline feature points, adopting a cubic spline interpolation algorithm to construct a continuous and smooth three-dimensional shoreline curve model, and fusing wharf geographic information to generate a shoreline visual map with geographic coordinates; establishing a ship coordinate system, converting inertial navigation attitude data into the coordinate system through a rotation matrix and a translation vector, fusing the inertial navigation attitude data with RTK position data, and outputting a high-precision ship pose; fusion data are transmitted through a 5G network, a shore end converts the fusion data into a local plane coordinate system and generates a real-time dynamic visual interface, the real-time dynamic visual interface is pushed to a tug terminal through an RTSP protocol, water diversion operation is assisted, high-precision perception, visual guidance and shore ship cooperation of the ship berthing process are achieved, and the water diversion safety and the intelligent level are improved.

The invention provides a network abnormal traffic identification method and system applied to big data, and the method comprises the steps: receiving an original traffic data stream flowing in a network transmission link, and extracting the associated attribute information carried by the original traffic data stream; performing link association analysis processing on the original traffic data flow to obtain a traffic association map and traffic transmission link characteristics; and inputting the traffic association map and the traffic transmission link features into a preset anomaly identification network, and generating traffic anomaly association features through hierarchical interaction processing. And triggering a classification decision-making mechanism based on the traffic anomaly association features, and outputting an anomaly identification result of the network traffic. And finally, generating flow control guide information according to an abnormal identification result, and sending the flow control guide information to a flow control node to execute a control operation. According to the method, flow data are analyzed from multiple dimensions, association between features is fully mined, accurate identification and effective management and control are realized, the capability of the network to deal with abnormal flow is effectively improved, and stable operation of the network and data security are guaranteed.

The invention relates to a ship mail adaptive coding and dynamic bandwidth allocation method, belongs to mobile voice service, mobile data communication service and other telecommunication services, and particularly relates to the field of digital information transmission. The method comprises the following steps: intelligently predicting the total number of transmitted mails and the total number of transmitted mail data of a target ship in a current time segment by using an AI network data prediction model according to various basic data which are fully and comprehensively selected; and determining an adaptive coding strategy and a dynamic bandwidth allocation strategy for the current time segment of the target ship based on the intelligent prediction result. According to the invention, in order to solve the technical problems that effective and smooth transmission of all mail data of each future time segment of each ship is difficult to consider and the utilization rate of network transmission resources is difficult to improve, A I network data prediction models of different structures customized and designed for different ships are used; and intelligent prediction of the mail transmission state of each ship in the future time segment is completed, so that the technical problem is solved.

The invention discloses an audio and video processing system and method supporting an AI intelligent repair technology, and relates to the technical field of audio and video data processing, and the method comprises the following steps: carrying out the scene recognition based on a playing source type, a user interaction form, an audio and video code rate, an audio sampling rate and network transmission time delay, and generating live broadcast, film watching and singing scene labels; determining a time delay upper limit, a resolution target, a detail reduction level, an audio fidelity index and a beat alignment threshold according to the scene label, and forming a performance constraint vector; according to the invention, a closed-loop mechanism of scene identification, performance constraint setting, repair link arrangement, cloud and terminal task allocation, real-time adaptive adjustment and parameter iterative optimization is constructed for different requirements of live broadcast, film watching, singing and other scenes, so that low delay, high image quality, high tone quality and computing power adaptation are realized; and the stability and the continuous optimization capability of the system are improved through versioning and staged release.

The invention discloses a high-concurrency virtual service transfer scheduling method and system based on a cloud edge collaborative architecture, and relates to the technical field of cloud computing and edge computing collaboration, and the method comprises the steps: constructing a service gene analysis model at an edge node, responding to a virtual service access request, extracting the resource consumption characteristics of a service flow in real time, and calculating a service separation potential energy index. The virtual business is dynamically decoupled into a connection anchoring phase and a computing power free phase based on the index; establishing a load inertia monitoring mechanism, modeling resource consumption of edge nodes into a kinematics system, collecting speed and acceleration of load change in real time, calculating system pressure momentum, and generating a graded unloading instruction when the momentum exceeds a preset critical collapse threshold value; starting a convergent differential injection mechanism, pre-constructing a logic shadow at a cloud end, and calculating a convergence ratio of a memory dirty page generation rate to a network transmission rate in real time; the method has the advantages of being high in practicability, having the pre-judgment capacity and being capable of achieving lossless switching.

The invention relates to a vehicle priority passing control method based on a transportation task. The method comprises the steps that 1, a vehicle transmits collected vehicle basic driving data to a collection gateway through a network; step 2, the acquisition gateway performs deserialization and cleaning processing on the received data for subsequent data processing; step 3, extracting the processed data, constructing a lane buffer area, identifying a corresponding relation between the vehicle and the lane, obtaining lane-associated traffic light phase information, and judging whether traffic lights are in front of the vehicle; step 4, if no traffic light exists in front, positioning the lane where the vehicle is located according to the vehicle GPS information and the lane buffer area, and judging whether other vehicles exist in front of the vehicle or not; and 5, if other vehicles exist in front, carrying out priority ranking on the vehicles according to the vehicle transportation task emergency degree and the task deadline urgency degree, and if the priority of the front vehicle is low, generating a way giving instruction for the front vehicle so as to allow the vehicle with the high priority to pass preferentially.

The invention discloses an intelligent and safe electricity utilization safety monitoring system which comprises an intelligent sensing layer, a network transmission layer, a cloud processing layer and a user interaction layer. The intelligent sensing layer comprises a plurality of intelligent sensor units, the intelligent sensor units are installed on power distribution equipment and used for collecting real-time parameters in real time, and the real-time parameters comprise current, voltage, electric leakage, temperature and fault arc parameters of a line; the network transmission layer is used for transmitting parameters and abnormal alarm information acquired by the intelligent sensor unit to the cloud processing layer; the cloud processing layer receives and stores the real-time parameters, and analyzes and processes the real-time parameters; and the user interaction layer is in communication connection with the cloud processing layer, and is used for a user to check parameters, receive an alarm notification and remotely control related equipment. According to the invention, more intelligent power utilization safety monitoring can be carried out.

The invention relates to the technical field of machine room monitoring, in particular to an intelligent machine room monitoring system and method based on the Internet of Things. According to the method, the visible light and infrared images are fused, so that the detection precision and robustness of the target in a complex environment are improved, and the limitation of single-mode imaging in illumination variation, shielding or extreme environments is effectively overcome. Meanwhile, by combining RFID identity recognition and space-time correlation analysis of a visual track, accurate matching of the personnel and the equipment is realized, the identity recognition accuracy and behavior discrimination reliability of the target personnel, tools or equipment are remarkably improved, and the risk of misinformation and missing report is effectively reduced. According to the invention, localization processing is carried out on the multi-source data through edge calculation, network transmission delay and bandwidth pressure are effectively reduced, and the response speed and stability of the system are improved.

The invention discloses a vehicle-mounted Ethernet TSN network performance test system and method. The system comprises a plurality of vehicle-mounted Ethernet simulators, a passive TAP test tool, a flow generation module and a feature rule matching module. The plurality of vehicle-mounted Ethernet simulators are used for simulating a plurality of application vehicle-mounted terminals, the traffic generation module generates specific data streams and sends the specific data streams to the application vehicle-mounted terminals, and the specific data streams are forwarded to a target application vehicle-mounted terminal through a TSN network; the passive TAP test tool obtains a mixed data stream formed by the sent and received data streams; and the characteristic rule matching module is used for matching the specific data stream with the obtained mixed data stream to obtain time information of the specific data stream reaching the corresponding TAP test point location, and calculating to obtain a performance index of the TSN network by comparing the sending time of the specific data stream with the time of the specific data stream reaching the corresponding TAP test point location. According to the invention, the non-inductive test of the TSN network can be realized, and the network transmission performance of the TSN network can be accurately obtained.

The invention relates to a vehicle OTA upgrading method and system based on regional feature perception and a medium, and relates to the technical field of new energy vehicle remote upgrade.The method comprises the steps that on the basis of multi-dimensional environment parameters of all regions of the global, the global is divided into a plurality of regional feature clusters through a density clustering algorithm; for each regional feature cluster, generating an increment upgrade package containing a regional environment feature matrix through binary difference analysis; dynamically selecting an optimal network transmission path based on transmission cost, packet loss rate and time delay parameters of a cellular network, a Wi-Fi hotspot and satellite communication; and sending the incremental upgrade package to a vehicle in a target area through the optimal network transmission path to carry out OTA upgrade. According to the method, the traffic cost and the failure rate of transnational OTA upgrading can be remarkably reduced, and meanwhile, the reliability and the efficiency of vehicle software updating in different geographical environments are improved.

The invention provides a system, a method and a device for monitoring the operation state of production equipment. The method comprises the following steps: determining total operation time data of the production equipment based on a startup signal; receiving production data pushed by production software corresponding to the production equipment; capturing an interface image of the production software, and generating a production state identifier and actual production time data of the production equipment after image recognition; calculating and generating estimated power consumption data; generating a state data packet with a uniform format and sending the state data packet to the MES subsystem; and outputting an equipment operation state report, an energy efficiency evaluation chart and a historical data query result according to the state data packet. According to the invention, equipment data acquisition is realized in a pure software mode, two modes of API docking and image recognition are supported to be compatible with new and old equipment, comprehensive, real-time and accurate equipment state data are provided for an MES system in combination with intelligent energy consumption estimation and a flexible network transmission strategy, the system reconstruction cost and complexity are significantly reduced, and the system reliability is improved. And the intelligent level of production management is improved.

A method of operating a communications device configured to transmit data via a wireless access interface is provided. The method comprises operating in accordance with a configured grant, CG, mode of operation comprising determining a sequence of instances of uplink communications resources of the wireless access interface and transmitting uplink data to the wireless communications network in at least one instance of the sequence of instances of uplink communications resources, transmitting, to the wireless communications network, uplink control information relating to the CG mode of operation, CG-UCI, comprising one or more indicators which indicate information required to support one or more of a plurality of services, the plurality of services including Ultra Reliable Low Latency Communications, URLLC, and transmitting the uplink data in accordance with the information required to support the one or more of the plurality of services indicated by the one or more indicators of the transmitted CG-UCI.