260results about "Error avoidance" patented technology

Techniques for managing resource constraints of a cloud environment are disclosed. A system receives a request to initiate a provisioning process for provisioning a first service in the cloud environment. The system determines a resource constraint associated with a resource that the first service utilizes. Based on the resource constraint, the system determines a set of candidate services that also utilize the resource as candidates for deprovisioning from the cloud environment. The system identifies respective service features of the set of candidate services and generates a ranking of the set of candidate services based on weighting metrics associated with the respective service features. Based on the ranking, the system selects a second service of the set of candidate services for deprovisioning from the cloud environment. The system deprovisions the second service to alleviate the resource constraint and then provisions the first service by executing the provisioning process.

The invention discloses a multi-mode induction display screen response method fusing voice interaction, and relates to the technical field of man-machine interaction, and the method comprises the following steps: in a user interaction process, calling a built-in sensor through an interface component real-time state monitoring mechanism, continuously monitoring a rendering process of a target interface component at a millisecond-level time granularity, and displaying the rendering process of the target interface component; collecting multi-dimensional availability state parameter information of the interface component; the method comprises the following steps: preprocessing collected interface component multi-dimensional availability state parameter information, and extracting key indexes reflecting potential asynchronous triggering risks from preprocessed data through a feature engineering method; by sensing the state of the interface component in real time, extracting the asynchronous risk index and combining machine learning recognition and TCN prediction modeling, dynamic regulation and control of the induction triggering window and the animation rhythm are achieved, the problem of mispointing or dislocation of the induction component is avoided, the accuracy and safety of interaction response are improved, and the user experience is improved. The method is suitable for high-precision scenes such as vehicle-mounted, medical and industrial control.

Systems and methods of loopback control in multi-active database synchronization are provided. A first database instance and a second database instance are configured with two-way synchronization. A synchronization tool detects a first log change in a first operation log associated with the first database instance. The first log change includes a first operation entry associated with a first data operation on a first data record in the first database instance. The first data record includes a first synchronization tag field comprising a first source tag representing a first data source associated with the first data operation on the first data record. If the source tag contains the identification of the second database instance, the synchronization tool skips the first operation entry, without synchronizing the first data operation to the second database instance to avoid data loopback.

Systems and methods for real-time mapping and visualization generation of system components. The system may receive a first user request to generate a first visualization of a first configuration of a first subset of components in a first software system. The system may, in response to the first user request, retrieve a first software applications lineage log, wherein the first software applications lineage log comprises a log of event data of current processes being performed in the first software system. The system may generate a first feature input based on the first software applications lineage log. The system may input the first feature input into a first artificial intelligence model to generate a first output.

A system and method for assessing, broadcasting and remediating a health of a cloud computing infrastructure. A system includes a health assessment platform interfaced with components of the cloud computing infrastructure, and configured to perform an evaluation loop of the cloud computing infrastructure to produce a health assessment, the evaluation loop assessing one or more of a drift between desired and actual states, resource utilization, cost or spend controls, policy compliance, and planning or refactoring of the components of the cloud computing infrastructure. The health assessment platform is further configured to report the health assessment via notifications to a user interface associated with the cloud computing infrastructure. The system further includes a remediation engine that is interfaced with the user interface, the remediation engine configured to provide a user of the user interface with remediation recommendations and optimizations based on the reported health assessment.

A system and method for detecting code intent of code objects in a computing environment for assessing cybersecurity risk is presented. The method includes detecting a plurality of code objects in a computing environment; statically analyzing each code object of the plurality of code objects to determine a plurality of potential intents, each potential intent corresponding to an action; generating a cybersecurity signal in the computing environment based on a plurality of event records; detecting in the cybersecurity signal a first event corresponding to a potential intent; determining that the potential intent is a code intent based on the detection; detecting in the cybersecurity signal a second event which does not correspond to any potential intent; and initiating a remediation action in the computing environment based on the detected second event.

Methods and articles of manufacture for hosting a safety critical application on an uncontrolled data processing device are provided. Various checks and combinations of checks including installation, functional, host integrity, coexistence, interoperability, power management, and environment checks are performed at various times to determine if the safety critical application operates properly on the device. The operation of the SCA on the UDPD may be controlled accordingly.

A system and method for fail-operational mission continuity in a multi-agent autonomous system. Each autonomous agent includes an onboard Prognostic Health Management (PHM) module that monitors health using sensor data. Upon detecting an incipient fault, the PHM module calculates a prognostic Remaining Useful Life (RUL). This RUL is transformed into a quantitative Operational Risk Cost (Ω) and communicated to a multi-agent control system. The control system's dynamic task allocation algorithm uses the Ω values as key inputs in a multi-objective optimization process. This enables the system to proactively and autonomously re-allocate a task from a degrading agent to a healthy agent before a failure occurs. The degrading agent is simultaneously commanded to perform a safe contingency maneuver. This integration of real-time prognostics and multi-agent control creates a resilient, self-healing system capable of completing missions despite hardware degradation.

The present invention introduces an advanced system and method for predictive maintenance and fault detection, leveraging the synergistic potential of quantum computing and graph transformer networks. This innovation collects and preprocesses data from diverse sources through edge computing, enriching this data with supplemental information to construct a comprehensive operational dataset. Utilizing an ontology-based framework, the system organizes the data into a knowledge graph, which is then analyzed using quantum computing techniques to uncover complex, correlated relationships. The extracted relationships are further analyzed by a Graph Transformer Network (GTN) equipped with a multi-head attention mechanism, enabling the identification of spatio-temporal patterns indicative of potential system faults. The system classifies these patterns to distinguish between normal operation, potential faults, and outliers, facilitating proactive maintenance actions. This invention represents a significant advancement in the field of predictive maintenance, offering improved reliability, efficiency, and operational insight for complex systems.

Disclosed is an inter-channel interference attenuation circuit system, which includes a plurality of channels provided between a memory and a processor and that transmits data received from the memory to the processor, and an interference attenuation circuit module connected one by one to each of the channels, and each of the channels is, a victim channel with respect to the connected interference attenuation circuit module, and an aggressive channel with respect to an adjacent interference attenuation circuit module, which is an interference attenuation circuit module connected to an adjacent channel which is interfered with by its own data transmission, and each of the interference attenuation circuit modules, adjusts an output signal of the connected victim channel based on the interference attenuation circuit module and the number of adjacent channels.

A data processing method includes starting, based on a state of a cache line in a memory changing from a non-modified state to a modified state, a timer of the cache line; and writing the cache line back to a next-level memory when the timer of the cache line expires such that the cache line does not remain in the modified state for a long time. When the timer of the cache line expires, the cache line is written back to the next-level memory, and data of the cache line is backed up.

Methods, systems, and products for health signature based load shifting for part longevity may include monitoring one or more variables associated with each of multiple redundant parts of a computing system, where one or more of the redundant parts are experiencing a load, generating, based on the monitored variables, a health signature for each of the redundant parts, and shifting, based on the health signatures, the load between the redundant parts.

Methods, systems and computer program products for bringing-up a computing cluster on a public cloud infrastructure with techniques utilizing expressed intents (high level descriptions of desired configuration) and asynchronously receiving configuration status messages from the public cloud infrastructure. The method includes a cloud management computing system transmitting to the public cloud infrastructure a first expressed intent for bringing-up a computing cluster. The cloud management computing system asynchronously receiving periodic status messages comprising cluster status data from the public cloud infrastructure reflecting a current configuration state of the computing cluster. The system determines, based on the cluster status data, whether the first expressed intent for the computing cluster has been achieved.

A system and method for anomaly prediction in a plurality of applications to maintain operability of the system. Real-time data from the plurality of applications can be received, and for each desired variable in the data an entropy that can indicate an anomaly in the respective data. The data can be divided into batches of fixes size and a plurality of machine learning (ML) models applied to each of the batches to determine whether the data contains an anomaly or is about to contain an anomaly. The plurality of ML models can be trained based on historical data from the plurality of applications. A large language model (LLM) can be applied to the output of the plurality of ML models to evaluate performance / fine tune the plurality of ML models, and an alert can be transmitted to a system that automatically executes script(s) to take action to avoid the anomaly.

A plurality of computing devices are communicatively coupled to each other via a network, and each of the plurality of computing devices is operably coupled to one or more of a plurality of storage devices. A plurality of failure resilient stripes is distributed across the plurality of storage devices such that each of the plurality of failure resilient stripes spans a plurality of the storage devices. A graphics processing unit is operable to access data files from the failure resilient stripes, while bypassing a kernel page cache. Furthermore, these data files may be accessed in parallel by the graphics processing unit.

The present disclosure includes apparatuses, methods, and systems for a radiation sensor suite. In an example, a method can include calibrating a plurality of sensors of a sensor suite located on a non-volatile memory die and monitoring for a plurality of radiation events at each one of the plurality of sensors. In response to none of the plurality of sensors detecting a radiation event, the method can include the sensor suite continuing to monitor for the plurality of radiation events. In response to at least one of the plurality of radiation sensors detecting a radiation event, the method can include notifying a host of the radiation event and identifying a NAND flash memory array region affected and correcting the radiation event based on the radiation event and the NAND flash memory array region affected.

The invention relates to the technical field of solid state disks, in particular to a solid state disk intelligent read-write optimization method based on artificial intelligence, comprising an intelligent read-write scheduler, adaptive wear leveling, read-write performance optimization, fault prediction and health management, and safety protection and efficiency improvement. The use mode is analyzed through a machine learning algorithm, the cache strategy is optimized, fault prediction is carried out, the read-write performance and the data safety are improved, the read-write speed, stability and safety of the solid state disk can be remarkably improved, the requirements of diversified application scenes are met, faults are predicted, and the phenomenon that the solid state disk breaks down is avoided; through intelligent read-write optimization driven by artificial intelligence, the SSD can realize collaborative optimization of performance, service life and energy efficiency under a complex load, a high-reliability storage solution is provided for scenes such as a data center and edge computing, and the performance, service life and energy efficiency of the SSD can be improved by combining machine learning, reinforcement learning and a hardware collaborative technology.

Methods and systems for managing operations of a data processing system are disclosed. To manage operations of the data processing system, a management controller of the data processing system may obtain diagnostic data from hardware resources of the data processing system. The management controller may provide the diagnostic data to a device operation manager. The management controller may obtain a response from the device operation manager indicating a level of anomalousness of the diagnostic data with respect to a baseline for the data processing system. In a first instance of the obtaining where the level of anomalousness meets criteria, the management controller may obtain an action set for updating the operation of the data processing system. The management controller may perform the action set to update an existing operating state of the data processing system to reduce a likelihood that a hardware resource becomes impaired.

A method for fault tolerant implementation of a mapping of at least one input value to at least one output value by a processing assembly with a plurality of processing units is disclosed. The mapping includes a plurality of structures with computational operations which can be evaluated by one or more of the processing units. Each of the structures is associated with criticality information that includes information how critical the error-free evaluation of the structure is for the error-free evaluation of the mapping. If at least one processing unit has a malfunction, at least one structure is selected based on the criticality information of the structures. It is determined whether the at least one structure should be evaluated in a modified manner or not evaluated. The mapping is applied to input values, wherein the selected at least one structure is evaluated in a modified manner or is not evaluated.

This disclosure describes techniques for intelligently detecting overheating devices in a network or data center and taking actions to address such overheating devices. This disclosure also describes evaluating heat dissipation information associated with components of devices in a network, making predictions about network disruptions based on the evaluation of the heat dissipation information, and taking actions to address, mitigate, or prevent such network disruptions. In one example, this disclosure describes a method that includes collecting, by a computing system, information about thermal metrics for a plurality of network devices; identifying, by the computing system and based on the information about the thermal metrics, a specific network device that changes temperature quickly; and taking action, by the computing system, to address effects of overheating associated with the specific network device.

Embodiments of this disclosure relate to methods, electronic devices, and computer program products for managing storage systems. The method includes determining whether the storage device failure will no longer occur based on reference values ​​of attribute parameters in a first set of the attribute parameters and current values ​​of attribute parameters in a second set of the attribute parameters, if it is determined that the storage device will fail based on current values ​​of multiple attribute parameters in the storage system. The method further includes determining the cause of the failure based on the attribute parameters in the first set if it is determined that the storage device failure will no longer occur. Embodiments of this disclosure can analyze the cause of storage device failure, thereby avoiding the erroneous identification of internally faulty storage devices as internally faulty ones.

The present invention provides a device and method for predicting the occurrence of failures in underground conduit networks. [Solution] The device includes a reading module configured to read connection data, the connection data including data indicating one or more pipe segments and data indicating one or more valves, where the end of each pipe segment is connected to the end of another pipe segment or a valve; a clustering module configured to automatically generate one or more clusters from the connection data, where each cluster includes pipe segments that form a connection network between valves; a cluster failure likelihood calculation module configured to calculate the failure likelihood of each cluster by summing the failure likelihoods of the pipe segments included in each cluster; and a display module configured to display the one or more clusters and the failure likelihood of each cluster on a display.

The invention discloses an operation and maintenance job task monitoring method, device and equipment, a storage medium and a product, which can be applied to the financial science and technology field, and the method comprises the steps: carrying out the machine operation state detection of at least one operation and maintenance production machine in the operation and maintenance job task execution process, and obtaining the machine operation state data; determining the operation and maintenance task interruption probability of each operation and maintenance production machine in a preset second time period according to the machine operation state data in the preset first time period; according to the operation and maintenance task interruption probability of each operation and maintenance production machine, if it is determined that a target production machine meeting a preset interruption decision judgment condition exists, generating a target machine execution strategy according to the operation and maintenance task interruption probability of the target production machine, and issuing the target machine execution strategy to the target production machine, and executing the target machine execution strategy by the target production machine. According to the technical scheme, risks such as interruption or abnormity in the operation and maintenance task execution process are monitored and evaluated in advance.

A system and related method, including a first processor core, a second processor core and a control circuitry to receive requests to update existing firmware of the first processor core to a new firmware. The control circuitry loads existing firmware onto the second processor core and migrates data associated with the existing firmware on the first processor core to the second processor core. The control circuitry stops the transaction execution by the first processor core while causing the second processor core to execute transactions in place of the first processor core. The control circuitry restarts the first processor core, replaces the existing firmware on the first processor core with the new firmware, and migrates data of the existing firmware on the second processor core to the first processor core. The control circuitry stops the transaction execution of the second processor core and causes the first processor core to execute transactions.

Embodiments of the present application disclose a wild pointer processing method, system, device and storage medium. According to the type information of each memory object, the technical solution provided by the embodiments of the present application determines the memory object of a specified type as a target memory object; then in the case of releasing the target memory object, a target zombie object is created, the instruction set architecture pointer of the target memory object is modified, and the instruction set architecture pointer is pointed to the target zombie object; and then the target zombie object is saved to the application memory, so that when the calling party uses the instruction set architecture pointer to call the target memory object, the calling party is intercepted based on the target zombie object through a message forwarding mechanism, and the calling logic is processed. By using the above technical means, the wild pointer processing of the online running environment of the application program can be realized, the application program can be prevented from crashing, the running effect of the application program is optimized, and the user experience is improved.

Provided are a method and an apparatus for monitoring a network system, and a computing device. The network system comprises at least one resource cluster. The method comprises: in response to a health degree display triggering event, displaying health degrees of a monitored object on a first display interface, different health degrees corresponding to different marks, wherein the monitored object comprises at least one of the following: the network system, one or a plurality of resource clusters in the at least one resource cluster, one or a plurality of resources comprised in the network system, or one or a plurality of services provided by the network system. The health degrees of various levels can be displayed, and a scientific basis can also be provided for the response time of the operation and maintenance personnel based on the different health degrees, so that rapid problem positioning can be achieved, thereby solving the management problem.

This application relates to the computer field, and provides a data restoration method and apparatus for a storage device, to implement data restoration without losing data after an attack by ransomware, and reduce performance overheads and storage space overheads. The method includes: A storage device stores data in append write mode; determines first data in response to inaccessibility to target data, where the first data is data marked as invalid, and is data associated with the target data; and restores the first data.

The application discloses a power button anti-misoperation control system, and relates to the control field, which comprises a baseboard management controller, a signal controller, a processor and a power button. The pressing time information of the power button of the equipment and the switch state of the anti-misoperation function are acquired. When the switch state is on, the preset time threshold is modified according to preset delay information to obtain an anti-misoperation threshold, and then the pressing time information is processed according to the switch state and the corresponding threshold to generate switch control information to control the shutdown or forced shutdown operation of the equipment. By setting the anti-misoperation function and adjusting the time threshold of triggering the shutdown or forced shutdown when the switch state is on, the pressing time required for triggering the corresponding operation is prolonged. Since the misoperation is usually short, it is difficult to reach the prolonged threshold, so that the abnormal shutdown of the equipment caused by the misoperation is effectively avoided. The technical problem that the abnormal shutdown of the equipment caused by the misoperation of the power button affects the business operation and causes losses is solved.

The invention relates to a method for calibrating a physical unit (12) and a system (10) for calibrating and adjusting a physical unit. The physical unit is arranged in the real process environment (14). A virtual component (26) disposed in a virtual process environment (24) is provided. The virtual process environment is formed to correspond to the real process environment such that the physical units arranged in the real process environment are represented in a manner corresponding to the virtual components (26) in the virtual process environment. Measurements are performed with a physical unit to obtain true measurements. The measurement is simulated with a virtual component to obtain a virtual measurement value. The offset is determined by a verification unit (30) based on a comparison of the real measurement and the virtual measurement. The real measurement value corresponds to the virtual measurement value. The physical unit is calibrated by the verification unit using at least the offset such that the compensation data based on the offset takes into account future measurements for the physical unit.