170 results about "Network component" patented technology

A machine learning model may be configured for training using an associated learning technique. A model configured for end-to-end backpropagation may adapted for associated learning by introducing functions for projecting hidden vectors and labels to a shared representation space and for reconstructing labels from representation vectors. An associated learning loss may be calculated at each layer, with the resulting gradients backpropagated locally through that layer rather than all layers. A reconstruction loss may be calculated using each layer's output including the predicted label. Training by associated learning may be parallelized (e.g., layer by layer) to yield efficiency gains. In addition, associated learning training may be more robust to training label errors. The resulting model may be used to, for example, predict data sequences in an autoregressive manner in which subsequent portions of the output data sequence are predicted in part based on previous predicted portions of the output data sequence.

An apparatus is configured to communicate with multiple network components in a service-based architecture and comprises a memory and a processor. The memory stores multiple configuration commands. The processor is configured to generate a request to establish a communication session between a first network component, a second network component, and a third network component. The first network component exchanges connectivity signals with the second network component and the third network component. The second network component performs first plurality of session operations in response to the connectivity signals exchanged with the first network component. The second network component reports to the third network component that the first session operations are performed. The processor is further configured to, in response to determining that the communication session between the first network component and the second network component is lost, maintain the communication session between the first network component and the third network component.

A method for enhancing security of data, code, and / or network components by introducing a layer of integrity management that adapts to changing conditions within a network. The method may include use of a processor to perform intrusion analysis using an intrusion detection system and / or prevention system, behavioral analysis by accessing user logs to see if behavior is within a normal range, and / or geolocation analysis to see if the piece of data, section of code, and / or network component are within their usual surroundings. When there is a concern of a data breach, leak, and / or hack, the processor may initiate a response that detects other pieces of data, sections of code, and / or network components in proximity, initiates a self-destruct mechanism, triggers hardware to perform outside of operational specifications, and contains the spread of the data breach, leak, and / or hack through shutdown procedures, isolating affected systems, and / or alerting security personnel.

Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) or network component may select a measurement window type corresponding to the positioning reference signal (PRS) processing window (PPW) or a measurement gap (MG) for measurement processing of each instance of a positioning frequency layer (PFL) for a positioning session of the UE based on one or more selection criteria.

A communication network configured to support time-sensitive interconnection communication is disclosed. In one example, the communication network comprises: communication network components, each configured to provide a functionality for data communication from a source device across the communication network to a destination device and a processor arranged to configure at least one component of the communication network components based on a time sensitive communication schedule of a flow which passes through the at least one component, wherein the at least one component is configured to act as at least one waypoint to provide the time sensitive interconnection communication such that the at least one waypoint communicates with at least one of other waypoints in a neighbor communication network to connect the time sensitive communication schedule with another time sensitive communication schedule of another flow passing through a plurality of other communication network components in the neighbor communication network.

In one implementation, a device may detect a drop in an amount of agents reporting network measurements for a network component; identify, based on network measurements from before and at a time of the drop, a network component set associated with the drop; generate, based on the network component set, a pseudo-measurement to represent absent data associated with the drop; and provide the pseudo-measurement as an input for root cause analysis.

Systems and techniques include identifying a network layer for performing a memory operation, identifying a subset of a plurality of configuration bit clusters of a non-volatile distributed memory that are mapped to the identified network layer using a cluster mapping, in response to identifying the subset of the plurality of configuration bit clusters, activating the subset of the plurality of configuration bit clusters, loading network component data from the subset of the plurality of configuration bit clusters into a local buffer, and applying the network component data to the network layer for performing the memory operation.

Systems, computer program products, and methods are described herein for automatic adjustment of network device configurations. The present disclosure is configured to receive a network device comprising a set of adjustable settings configured to adapt to a network assembly, wherein the network assembly comprises a plurality of network devices, wherein the set of adjustable settings within the network device can be adjusted to the network assembly and components within the network assembly; designate a function of the network device with respect to the network assembly; match the function of the network device with a model configuration plan associated with the network assembly via a machine learning model (MLM); configure the set of adjustable settings within the network device using the model configuration plan via the MLM to operably connect with the plurality of network devices within the network assembly.

Systems and methods for network communication degradation are disclosed. The system includes one or more processors configured to monitor network traffic associated with one or more devices to identify communication patterns. Upon detecting a predefined communication pattern in the monitored network traffic, the system generates a blocking event configured to degrade the network traffic associated with a specific application or service. The system implements the blocking event by instructing one or more network components to degrade the network traffic related to the specific application or service. This degradation reduces communication quality over a predefined temporal period.

Disclosed are a network interface card device, a network data transmission method, apparatus, and system, a device, and a medium, which are applied to the field of Internet technologies. The network interface card device includes a programmable device, which constructs a network platform based on a memory expansion method, and the network platform includes a network interface, a target memory, and a network component. The programmable device is connected to a network through the network interface, and exchanges data with a host by the memory expansion method. The host, based on the memory expansion method, configures the target memory of the programmable device as an extended memory of the host, for storing received target network data belonging to a network interface card processed packet type, or to-be-sent network data of the host.

Aspects of the disclosure are directed to training data requests associated with artificial intelligence machine learning (AIML) models. In an aspect, a device transmits, to a network component, an AIML model training data request that comprises an indication of AIML model training data preference(s) or requirement(s). The network component transmits, to the device in response to the request, AIML model training data based on the AIML model training data preference(s) or requirement(s). Note that the network component need not be the data source that measures the AIML model training data, and the AIML model training data may be collected before and / or after the AIML model training data request. Such aspects may provide various technical advantages, such as improving the quality of AIML training data which in turn increases the AIML model quality, which may be improve positioning, sensing, beam management, channel state information (CSI) procedures, and so on.

A reduced capability (redcap) user equipment (UE) is configured to receive a positioning reference signal (PRS) configuration from a network component and perform one or more positioning operations based at least in part on the PRS configuration. A base station is configured to receive a positioning reference signal (PRS) configuration for a reduced capability user equipment (redcap UE) from a location management function (LMF) of a network and transmit PRS to the redcap UE based on the PRS configuration.

Methods, systems, and devices for wireless communications are described. A wireless communications system may support immersive applications such as extended reality, mixed reality, interactive mapping, integration of artificial intelligence, among other services which may utilize high quality and low latency video streams. To support improved integration between network components providing applications, and to increase quality of experience (QoE) for users, the wireless communications system may implement radio access network (RAN)-assisted QoE-aware source bitrate selection. In some aspects, an application server may provide a RAN node with bitrate information for one or more users, including at least a first bitrate that maintains a threshold QoE for a threshold duration. The RAN node may determine, based on various factors such as network load, load balancing, obtainable QoE across users, among other factors, a selected bitrate for the one or more users and may provide the selected bitrate to the application server.

This invention discloses a daily runoff prediction method based on the Long Short-Term Component Neural Network (LSTCNet) model. LSTCNet leverages the advantages of convolutional layers to extract features. An attention mechanism (AM) is introduced in the long-term component to automatically select relative times across all time steps of the long-term data. The short-term component utilizes a multi-layer residual structure to fuse multi-level features from the short-term data, effectively improving model performance. Furthermore, a traditional AR model is used as a linear neural network component to enhance the learning of linear dependencies between variables and modify the output prediction values. Experimental results show that the proposed method has good performance in daily runoff prediction; the long-term and short-term components can effectively learn from their respective data, demonstrating the strength of the ensemble model.

A multi-domain recovery service (MDRS) is described for dynamically recovering from network path failures in a communication network. The MDRS can be implemented within an orchestrator of an Open Radio Access Network (O-RAN) architecture.Upon detecting a trigger condition affecting (e.g., a failure in) a network path that traverses multiple network domains, embodiments query a network topology service and an observability service to obtain high-level and low-level network topology information and real-time network conditions across these domains. Embodiments identify candidate alternative paths by analyzing this comprehensive network data and selects an optimal alternative path based on predefined criteria such as latency, bandwidth capacity, reliability, and traffic load. The orchestrator can then direct the reconfiguration of network components across the multiple network domains to route communications through the new network path, thereby restoring end-to-end connectivity.

The invention discloses a traffic monitoring method and device, and relates to the technical field of big data. A specific embodiment of the method comprises the following steps: creating a network traffic acquisition component, and modifying a source code of a browser network component in an original operating system of a to-be-monitored device, so that the to-be-monitored device calls the network traffic acquisition component; recompiling the modified source code of the browser network component and the network flow collection component to obtain a customized operating system; and intercepting network flow data of the to-be-monitored equipment based on the customized operating system, so as to monitor the to-be-monitored equipment according to the network flow data. According to the method, the source code of the browser network component in the original operating system of the to-be-monitored equipment is modified, the customized operating system is compiled, and the network traffic data of the to-be-monitored equipment is intercepted by using the customized operating system, so that agent software does not need to be installed, the operation is simple, and the traffic monitoring cost is reduced.

The application relates to the technical field of intelligent regulation and control of an archive storage environment, and discloses an intelligent control system for the temperature and humidity of an archive room. The system comprises an environment monitoring network component, an internal detection engine component, a fusion computing center component and a decision generator component. The environment monitoring network component collects environment data by using a sensor array and generates a high-precision environment state atlas by applying a data assimilation technique. The internal detection engine component reconstructs an internal non-uniform humidity field of archives based on risk identification in the atlas by using a waveform analysis algorithm. The fusion computing center component aligns the time and space attributes of the two, and outputs a comprehensive confidence by using an evidence reasoning method. The decision generator component generates an adaptive control strategy by using a heuristic optimization algorithm according to the confidence. The application realizes all-round accurate perception and intelligent regulation and control from the macro environment of the archive room to the micro environment of the archive entity.

Techniques for wireless sensing and / or communication are disclosed. In an aspect, a user equipment (UE) transmits a joint communication and sensing (JCS) transmit power capability of the UE, the joint communication and sensing (JCS) transmit power capability associated with a sensing operation of the UE, a communication operation of the UE, or both; and performing a sensing operation and a communication operation according to the JCS transmit power capability. In another aspect, a network component receives an indication of a JCS transmit power capability of a UE, and transmits a sensed power configuration based on the JCS transmit power capability of the UE.

The present disclosure relates to a computer-implemented method (100) for time validation in a network system (200), comprising: - Receiving (110), in a network component (210), a first global time (t1) of the network system (200) to a first local time (T1) of the network component (210) for a synchronization event; - Forwarding (120), through the network component (210), a second global time (t2) of the network system (200) to a second local time (T2) of the network component (210) for the synchronization event; - Determine (130), by the network component (210) or a validation unit (220), a first difference (Δ1) between the second local time (T2) and the first local time (T1); and - Performing (140), through the validation unit (220), a time validation with respect to the network component (210) based on the first difference (Δ1).

The invention discloses an underground coal mine intelligent illumination control system, which belongs to the technical field of underground coal mine automatic control, and comprises a terminal device group used for executing an illumination on-off control instruction and feeding back self running state data; the underground coal mine intelligent illumination control terminal establishes data interaction connection with the terminal equipment group, and a unique illumination control module is integrated in the underground coal mine intelligent illumination control terminal; the intelligent lighting control server group is in communication connection with the underground coal mine intelligent lighting control terminal; the communication network component is used for building a bidirectional data transmission link between the underground coal mine intelligent illumination control terminal and the intelligent illumination control server group by utilizing an existing underground coal mine looped network; by setting personnel and vehicle positioning data, traditional long-term lighting control is avoided, lighting of manned vehicles and lighting of unmanned vehicles are achieved, lighting according to needs is achieved, green construction of underground coal mine auxiliary transportation is greatly improved, electric power is saved, and the service life of lamps is prolonged.

The invention relates to the technical field of industrial detection, and discloses a conveyor belt deviation detection method and system, and the method constructs a complete intelligent deviation detection and control system through the technical means of multi-source information fusion, a physical constraint neural network, benchmark evolution modeling, comprehensive health degree evaluation, self-adaptive prediction control, and grading abnormity processing. Compared with a single position detection and fixed reference method in the prior art, the method realizes technical spanning from single-dimensional perception to multi-dimensional coordination, from rough measurement to fine decoupling, from fixed reference to dynamic self-adaption, from passive response to active prediction, and from open-loop control to closed-loop self-adaption; the neural network component decomposition process is constrained through a physical model, the accuracy of deviation detection is improved, and the probability of occurrence of misinformation and missing detection is reduced through a reference dynamic management mechanism.

This disclosure relates generally to image coding and particularly to methods and systems for neural image compression (NIC). The disclosed NIC decoder / encoder may include various neural network components that are configured to achieve a balance between network complexity and coding efficiency. Such a NIC decoder / encoder implementation particularly include a core decoder and a hyper decoder each including a neural network architecture adapted for achieving a lightweight decoder / encoder.

Example embodiments are directed towards systems and methods for model-based inventory of wireless telecommunication networks. In response to receiving information regarding network components or connectivity as system components are implemented (e.g., installed and / or activated), the system may electronically compare the received information to a model previously built according to the current standards of the telecommunication service provider, such as a mobile network operator (MNO) for the wireless telecommunication network, and then electronically determine whether there exists a discrepancy between the received information regarding network components or connectivity and the model based on the comparison. An action may then be performed based on the determination of whether there exists a discrepancy, such as sending an alert or taking other corrective action.

Systems and methods of managing network function routing perform or comprise determining that a first network node has been rendered inoperable, wherein the first network node is associated with a first Session Management Function (SMF); retrieving a list of tracking area codes (TACs), the list of TACs corresponding to one or more network components serviced by the first network node via a second network node, wherein the second network node is associated with an Access and Mobility Management Function (AMF); transmitting the list of TACs to a third network node, wherein the third network node is associated with a second SMF; and causing the second network node to clear its cache.

This invention discloses a network data processing method, terminal, storage medium, and processor, belonging to the field of cloud network technology. The network data processing method includes: acquiring at least one network component corresponding to a target instance; collecting time-series data from the at least one network component; determining the attribute information of the target instance based on the collected time-series data and / or the geographical location of the network component from which the time-series data originates, wherein the attribute information includes: time attributes corresponding to indicators; acquiring at least one of the following: configuration information of the target instance itself, configuration information of the network components, connection relationship information between at least one network component, and connection relationship information between the target instance and at least one network component; and establishing a model of the target instance based on the attribute information and configuration information, wherein the model is used to display the network information of the target instance. This invention solves the technical problem of the difficulty in acquiring and understanding network data in the prior art.

Apparatus and methods for discovery, synchronization and operation of network components. In one embodiment, the network comprises a passive optical network (PON), and the components being synchronized include an enhanced OLT (eOLT) and one or more enhanced ONUs (eONUs). The eOLT is configured in one variant to utilize control protocol messaging (such as those used in the MPCP or Multi Point Control Protocol) to communicate particular synchronization parameters and durations to the eONU(s), whether individually or via multicast / broadcast. The synchronization parameter and durations are selected to optimize discovery and synchronization of the eONU(s) with the eOLT, and also optimize (subsequent) normal operation, in one implementation through selection of synchronization patterns which enable most efficient AGC determination, clock recovery (CDR), SBD, and EBD identification.

In one embodiment, a method includes determining, by a first network component, a sender shaper drop value based on the following: a maximum sequence number; a minimum sequence number; and a sender sequence counter number associated with the first network component. The method also includes determining, by the first network component, a wide area network (WAN) link drop value based on the sender sequence counter number associated with the first network component and a receiver sequence counter number associated with a second network component. The method further includes determining, by the first network component, whether to adjust a sender shaper rate based on the sender shaper drop value and the WAN link drop value.

A multi-domain recovery service (MDRS) is described for dynamically recovering from network path failures in a communication network. The MDRS can be implemented within an orchestrator of an Open Radio Access Network (O-RAN) architecture. Upon detecting a trigger condition affecting (e.g., a failure in) a network path that traverses multiple network domains, embodiments query a network topology service and an observability service to obtain high-level and low-level network topology information and real-time network conditions across these domains. Embodiments identify candidate alternative paths by analyzing this comprehensive network data and selects an optimal alternative path based on predefined criteria such as latency, bandwidth capacity, reliability, and traffic load. The orchestrator can then direct the reconfiguration of network components across the multiple network domains to route communications through the new network path, thereby restoring end-to-end connectivity.

This disclosure relates to a fully software-defined, fully virtualized, and customizable mobile communication platform deployed on public cloud infrastructure. Such mobile networks allows for end to end control of automatic and programmatic deployment and configuration of the mobile network components. The implementations below effectively enables instant creation and deployment of a true private global end-to-end Software Defined Network (SDN) for 3G, 4G, LTE, and 5G mobile communication from the ground up. Users will effectively act their own mobile carrier, allowing them to customize the features available to them via a programmatic interface.