Abstract: Techniques for orchestrating a workflow for configuring a computer networking environment or other complex workflows are described. A Directed Acyclic Graph (DAG) that defines a plurality of tasks to be executed to complete the workflow and a plurality of orders between the tasks is received. Embodiments generate a State-Machine Neural Network (SNN) based on the received DAG, by generating a plurality of SNN neurons for the SNN, based on the plurality of tasks within the received DAG and generating a plurality of SNN connections for the SNN, connecting pairs of SNN neurons within the plurality of SNN neurons, based on the plurality of connections within the received DAG. The SNN is executed to orchestrate the workflow by sending and receiving signals to and from the SNN neurons.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for memory fault prediction. In a method for memory fault prediction provided by the embodiments of the present disclosure, an accuracy of fault prediction over a past period of time is obtained, each fault prediction is made based on a comparison of a prediction confidence with a confidence threshold, and the accuracy indicates an amount of work to reconstruct and diagnose predicted faulty memories after the fault prediction; the confidence threshold is adjusted in response to the accuracy being less than an accuracy threshold; a detection rate of the fault prediction over the past period of time is obtained; and the confidence threshold is adjusted reversely in response to the detection rate being less than a detection rate threshold. In this way, the reliability of memories in nodes is guaranteed while reducing unnecessary reconstructions and diagnoses.

Abstract: In general, in one aspect, the invention relates to a method for enabling enhanced logging. The method includes obtaining a log associated with a job; determining, using the log, that enhanced logging is to be enabled prior to initiating the job; enabling, in response to the determination, enhanced logging on at least one node, and initiating servicing of the job, after the enabling, on the at least one node.

Abstract: A system, method and computer program product collects and provides for display operational status data in several levels of detail about multiple client computer systems.

Abstract: The invention relates to a fault diagnosis method for a rolling bearing under variable working conditions. Based on a convolutional neural network, a transfer learning algorithm is combined to handle the problem of the reduced universality of deep learning models. Data acquired under different working conditions is segmented to obtain samples. The samples are preprocessed by using FFT. Low-level features of the samples are extracted by using improved ResNet-50, and a multi-scale feature extractor analyzes the low-level features to obtain high-level features as inputs of a classifier. In a training process, high-level features of training samples and test samples are extracted, and a conditional distribution distance between them is calculated as a part of a target function for backpropagation to implement intra-class adaptation, thereby reducing the impact of domain shift, to enable a deep learning model to better carry out fault diagnosis tasks.

Abstract: The disclosed embodiments provide a method and system for processing network data. During operation, the system obtains, at a remote capture agent, configuration information for the remote capture agent from a configuration server over a network. Next, the system uses the configuration information to configure the generation of event data from network data obtained from network packets at the remote capture agent. The system then uses the configuration information to configure transformation of the event data or the network data into transformed event data at the remote capture agent.

Abstract: Methods, apparatus, systems, and articles of manufacture to provide tenant aware runtime feature toggling in a cloud or other virtualized computing environment are disclosed. An example method includes determining a feature toggle associated with a resource of a provisioning request; retrieving the feature toggle from a database using a first tenant identifier, the feature toggle to have a first value for the first tenant identifier and a second value for a second tenant identifier; processing the feature toggle to provision the resource according to the first value of the feature toggle; and facilitating provisioning of the resource according to the first value.

Abstract: Methods and systems are described herein for detecting anomalous access to system resources. An anomaly detection system may access system events from one or more computing devices and may generate entries from the system events. Each entry may include a corresponding timestamp indicating a time when a corresponding system event occurred, a corresponding user identifier indicating a user account within a computing environment associated with the corresponding system event, a corresponding location identifier indicating a location within the computing environment, and a corresponding action identifier indicating an action that the user account performed with respect to the location or an object within the computing environment. The generated entries may be aggregated and input into an anomaly detection model to obtain anomalous activity identified by the model.

Abstract: Aspects of the present disclosure relate to computer system security. A machine accesses a set of records corresponding to a set of users having access to a computer system. The machine stores, for each user in the set of users, a baseline profile representing baseline activity of the user with respect to a set of data sources of the computer system. The machine monitors activity of the set of users with respect to the set of data sources. The machine determines, based on monitoring the activity of the set of users, that a user action of a specified user, with respect to one or more data sources from the set of data sources, is anomalous relative to the baseline profile of the specified user. The machine provides a digital transmission representing the anomalous user action.

Abstract: A credit regulation and monitoring module receives a command for an application that is to be executed. In response to the command, credit amount for execution of the command is calculated. Further, an outstanding credit amount is determined based on an outstanding credit table and the other commands being executed. It is determined whether the credit amount and the outstanding credit are below a threshold value. If so, the command is executed and an outstanding credit table is updated to reduce the amount of credit available according to the credit amount allocated to the command.

Abstract: Granular performance analysis may be performed for database queries. Database query performance may be monitored. For some database queries, performance of portions of the database query may be measure. The measure performance of the portions may be compared with performance goals that correspond to the portions of the database query. Portions that do not meet or exceed the corresponding performance goals may be identified so that an indication of the identified portions may be provided.

Abstract: Methods and systems for managing data collection are disclosed. To manage data collection, a system may include a data aggregator and a data collector. The data aggregator and/or data collector may utilize inference models to predict the future operation of the data collector. To minimize data transmission, the data collector may transmit a representation of data to the data aggregator only if the representation of data falls outside a threshold. The threshold may be adapted by the data aggregator in response to the needs of downstream consumers of the data.

Abstract: It is presented a method for session analysis in a wireless communication network. The method is performed in a network node of the wireless communication network and comprises receiving a session report from a wireless terminal, the wireless terminal being within a coverage region of the wireless communication network, obtaining a network report associated with the session report, and storing a session network report associated with performance of the obtained network report and performance of the received the session report, for the coverage region. It is also presented a network node, a wireless terminal, a computer program and a computer program product thereof.

Abstract: An autonomous driving system includes: at least one sensor (1) configured to collect environment information around a vehicle; a primary decision unit (21) configured to calculate decision information based on the environment information collected by the at least one sensor (1), and transmit the decision information to a controller (3); an alternative decision unit (22) configured to calculate decision information based on the environment information collected by the at least one sensor (1) in response to detecting that the primary decision unit (21) is abnormal, and transmit the decision information to the controller (3); and the controller (3) configured to calculate vehicle control information based on the received decision information, and transmit the vehicle control information to a bottom vehicle controller. In this way, the stability and reliability of the autonomous driving system can be improved and safety of autonomous driving of the vehicle can be guaranteed.

Abstract: Methods, apparatus, and processor-readable storage media for automatically remediating storage device issues using machine learning techniques are provided herein. An example computer-implemented method includes obtaining performance-related information pertaining to one or more storage devices; automatically determining one or more workflows to be executed in connection with remediating at least one issue attributed to at least a portion of the one or more storage devices, wherein determining the one or more workflows comprises applying one or more machine learning techniques to the obtained performance-related information; and performing one or more automated actions based at least in part on the one or more workflows.

Abstract: A storage device includes a memory device including a plurality of memory blocks including a plurality of memory cells respectively connected to a plurality of word lines which are vertically stacked, and a memory controller configured to control the memory device to determine an attribute of a plurality of write data corresponding to a write request in response to the write request provided from a host, set a program voltage used for a program operation of storing write data having the same attribute of the write data among the plurality of write data in the same memory block based on a lookup table including the attribute of the write data and program information on the program voltage according to positions of the plurality of word lines, and perform the program operation according to the set program voltage.

Abstract: Disclosed embodiments are directed at systems, methods, and architecture for operating a control plan of a microservices application. The control plane corresponds with data plane proxies associated with each of a plurality of APIs that make up the microservices application. The communication between the data plane proxies and the control plane enables automatic detection of service groups of APIs and automatic repair of application performance in real-time in response to degrading service node conditions.

Abstract: The present invention proposes a method for managing a plurality of memory units in a flash memory module. The method includes: creating a programed timestamp corresponding to each first memory unit according to a data-written time of said each first memory unit; selecting a corresponding read-retry table for performing a read operation upon said each first memory unit according to the programed timestamp of said each first memory unit; and performing a first refresh operation according to program timestamps of first memory units that have been written with data.

Abstract: A system, method and apparatus for choosing a digital processing platform that is optimal for a specified type of application and satisfies a set of user-specified constraints is provided. In operation, all known parameters on all available processing platforms in a database are stored, providing this information to a computer software application run by the user by querying the database, and then allowing a remote user to specify the constraints, in terms of hardware and system software, to eliminate those entries that would not satisfy the constraints in a step-by-step filtering process. The user then chooses a set of application programs to run on the platforms that were not eliminated. The runtime performance parameters/characteristics—e.g. computational throughput, I/O bandwidth, environmental parameters, etc. are measured to select the optimal solution. The system and method also allows for a regression test to ensure consistency between test software processes running on discrete platforms.

Abstract: A method for execution by a dispersed storage and task (DST) client module includes issuing a read threshold number of read slice requests are issued to storage units of the set of storage units. One or more encoded slices of a selected read threshold number of encoded slices are received. When a next encoded data slice of a decode threshold number of encoded data slices is received within a response timeframe, outputting of the next encoded data slice is initiated. When the next encoded data slice is not received within the response timeframe, receiving of another decode threshold number of encoded slices of the set of encoded slices is facilitated. The other decode threshold number of encoded slices are decoded to produce recovered encoded data slices, where the recovered encoded data slices includes at least a recovered next encoded data. Outputting of the recovered next encoded data slice is initiated.

Abstract: Currently solutions for early detection of failures in manufacturing utilize predefined threshold levels of the process variables associated with equipment in manufacturing unit/industry plants. The pre-defined threshold and levels thereof are compared with the real values obtained from the manufacturing unit to check behavior of process variables (also referred as ‘process parameters’) and thus are prone to error. The present disclosure provides systems and method for predicting early warning of operating mode of equipment operating in industry plants which is based on transforming conditions on process parameters into conditions on corresponding fuzzy indices based on their thresholds. The fuzzy indices (concordance index, discordance index) of individual conditions are combined into a composite fuzzy index (composite index or degree of credibility) that describes the failure scenario in the process parameter space.

Abstract: A data collection system including a device having a communication function and a data collection apparatus configured to collect data transmitted from the device. The data collection apparatus includes a receiver configured to receive data transmitted from the device, a data analyzer configured to acquire analyzed data by analyzing the received data according to analysis data format different for each device, a first data storage which is a non-rewritable storage, a second data storage which is storage that can be accessed faster than the first data storage and that stores a smaller amount of data than the first data storage, a data writer configured to writes and stores the data received by the receiver to the first data storage, and writes and stores the analyzed data acquired by the data analyzer to the second data storage.

Abstract: The present disclosure provides techniques for composition enablement for extensibility of a system. The techniques include delivering an interface to a first downstream provider, where the interface includes a bean implementation format. Then performing at least one of: (i) receiving a provider level (POL) selection from the first downstream provider, where the POL selection corresponds to a POL stored in an extender, and delivering a first bean implementation to the first downstream provider based on the POL, and (ii) receiving a constructed bean implementation from the downstream provider, determining a POL of the downstream provider, and storing the constructed bean implementation in the extender at the determined POL.

Abstract: Data is received characterizing a plurality of virtual resources executing application code and deployed within a remote computing environment. The remote computing environment is providing a first configuration of computing resources for execution of the plurality of virtual resources. Resource consumption information associated with the plurality of virtual resources is monitored via an application programing interface of the remote computing environment. A second configuration of computing resources for the plurality of virtual resources is determined using a set of rules and the resource consumption information. A request is transmitted to the remote computing environment to provide the second configuration of computing resources for execution of the plurality of virtual resources. Related apparatus, systems, techniques and articles are also described.

Abstract: A method and a system for detecting anomalies that indicate potential system infrastructure problems is provided. The method includes: obtaining a first set of telemetry data that relates to a system infrastructure events, logs, and metrics that occur during a predetermined time interval; retrieving, from a memory, historical data that relates to system infrastructure telemetry; comparing the obtained first set of telemetry data with the retrieved historical data; detecting an anomaly based on a result of the comparing; and determining a potential system infrastructure problem based on the detected anomaly. The method may include using a machine learning algorithm to analyze the obtained first set of telemetry data; identify a pattern in the data; assign scores to the events included in the data; and use the pattern and/or the scores to detect the anomaly using an artificial intelligence (AI) model that is trained using the retrieved historical data.

Abstract: This disclosure relates to method and system for performing effective orchestration of cognitive functions (CFs) in a distributed heterogeneous communication network. In one embodiment, the method may include determining a fault or a performance issue and associated causes, related to a set of network slices in the distributed heterogeneous communication network or a set of services across the set of network slices, using CFs associated with each of the set of services or with each of the set of network slices. The method may further include determining possible resolutions for the fault or the performance issue based on the associated causes, identifying a resolution by evaluating each of the possible resolutions for at least one of a suitability to or an impact on the set of services or the set of network slices, and implementing the resolution on one or more affected network segments of the set of network slices.

Abstract: Systems and methods for predictive technology incident reduction are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for predictive technology incident reduction may include: (1) receiving a change record for a proposed change to a computer application or a computer network infrastructure; (2) analyzing the potential change for an adverse potential cross impact with another computer application or a computer system; (3) predicting a probability of failure and an impact of the proposed change using a model; (4) in response to a low predicted probability of failure, or a high predicted probability of failure with a low predicted impact: approving the proposed change; and implementing the proposed change; and (5) in response to a high predicted probability of failure and a high predicted impact, rejecting the proposed change.

Abstract: Systems and methods for monitoring states of operation of a computer environment can include one or more computer servers identifying a target asset of the computer environment and establishing a communication link with a computing device associated with the target asset. The one or more computer servers can determine a first set of parameters for profiling the target asset, transmit a first query for the first set of parameters to the computing device via the communication link, and receive one or more first parameter values corresponding to the first set of parameters responsive to the query. The one or more computer servers can compare the one or more first parameter values to one or more first criteria or threshold values, an determine a state of operation of the target asset based on the comparison. The state of operation can be indicative of an abnormal behavior associated with the target asset.

Abstract: In an approach for generating hardware failure labels, a processor receives sensor data from a plurality of sensors associated with a hardware system. A processor calculates an adaptive stress factor, wherein the adaptive stress factor is a dynamic selection model. A processor calculates an adaptive stress time window, wherein the adaptive stress time window is a spatial distribution of the adaptive stress factor. A processor calculates a relative duty cycle, wherein the relative duty cycle is a first function of an internal state of the hardware system, a type of input to the hardware system, the adaptive stress factor, and the adaptive stress time window. A processor generates a failure label, wherein the failure label is calculated as a second function of the relative duty cycle and a design duty cycle.

Abstract: Real time detection of cyber threats using behavioral analytics is disclosed. An example method includes obtaining, in real time, attributes for an entity within a population of entities, the attributes being indicative of entity behavior; building an entity probability model using the attributes and associated values collected over a period of time; and establishing a control portion of the entity probability model associated with a portion of the period of time. The example method includes comparing any of the entity attribute values and the entity probability model for other portions of the period of time to the control portion to identify one or more anomalous differences, and executing a remediation action based thereon. Some embodiments include determining a set comprising the anomalous differences and additional anomalous differences for the entity or the entity's peer group, and calculating the set's overall probability to determine if the entity is malicious.

Abstract: There is disclosed in one example a computing apparatus, including: a processor; a multilevel cache including a plurality of cache levels; a peripheral device configured to write data directly to a selected cache level; and a cache monitoring circuit, including a cache counter to track cache lines evicted from the selected cache level without being processed; and logic to provide a direct write policy according to the cache counter.

Abstract: Systems and methods are provided to retrieve or analyze usage data collected from a device or a facility where the device, optionally with devices are located, and identify useful features for making a diagnosis of the device. The diagnosis can be made before a system failure to reduce down time and inefficient use of the device, or after the system failure to expedite and facilitate diagnosis and repair. In addition to the usage data, such as energy and resource consumption, the system can also obtain information relating to the facility and the device's external environment which can be used for normalizing the usage data. Further, based on the diagnosis, the system can make suitable recommendations for repair, replacement, maintenance and upgrade.

Abstract: A virtualized trap receiver that virtualizes Simple Network Management Protocol (SNMP) agents and trap receivers over a set of virtual machines is provided. The virtualized trap receiver receives trap messages regarding a particular application running on one or more application servers. The virtualized trap receiver processes the received trap messages at one or more virtual machines. The virtualized trap receiver responds to a query by a network manager regarding an operation of the particular application on the application servers based on the processed trap messages.

Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for configuring service consoles based on service feature templates using a database system. In some implementations, a database of a database system storing service feature templates can be maintained. A request for a service console comprising a console component can be processed. A service feature template comprising a template console component corresponding to the console component can be identified. A set of CRM records can be identified. It can be determined that a user has access to the console component. A graphical representation of the service console can be displayed in a user interface on a display of a device of the user.

Abstract: Methods and systems for aggressive intent write request cancellation are disclosed. A method includes: generating an entry for data creation and generating a data object in view of the entry. Further, the method includes sending intent write requests to write a plurality of slices of the data object into dispersed storage (DS) units and determining whether or not a threshold number of the plurality of slices have been written into the DS units. Additionally, the method includes canceling at least one queued intent write request of the intent write requests corresponding to at least one unwritten slice of the plurality of slices in response to determining that the threshold number of the plurality of slices have been written into the DS units.

Abstract: A method for providing automatic suppression of an alert includes receiving a first error associated with a first dataset, the first dataset being among a plurality of datasets in a computer data environment, accessing dependency data that describes a set of dependencies between the first dataset and other datasets, examining the dependency data to automatically identify a second dataset from among the other datasets, the second dataset being a dataset on which the first dataset depends, accessing alert data for the computer data environment to determine whether an active alert for the second dataset provides an indication that the first error is redundant to a second error associated with the second dataset, and upon determining that the first error is redundant, suppressing transmission of the alert and storing data about suppressing transmission in a data structure.

Abstract: An intuitive information search method and device based on a displayed image and a computer readable recording medium thereof. The information search method based on an image displayed on a device includes recognizing a first input indicating a selection related to a plurality of objects included in the image, recognizing a second input indicating a search relationship between the selected plurality of objects, and searching for information based on the first input and the second input; and outputting found information through the device.

Abstract: A machine-readable medium may store instructions executable by a processing resource to access log data of an enterprise and extract time-series data of an enterprise entity from the log data. The time-series data may include measured feature values of a set of selected features over a series of time periods. The instructions may be further executable to train a predictive model specific to the enterprise entity using the time-series data, wherein the predictive model is to generate, for a particular time period, a predicted feature value for each of the selected features; access actual feature values of the enterprise entity for the particular time period; apply first-level deviation criteria to the actual feature value and the predicted feature value of each selected feature to identify deviant features of the enterprise entity; and apply second-level deviation criteria to the identified deviant features to identify the enterprise entity as behaving abnormally.

Abstract: A method, computer program product, and computing system for receiving telemetry data associated with a plurality of storage devices. A storage device reliability level may be defined for each storage device based upon, at least in part, the telemetry data associated with the plurality of storage devices. Each storage device may be partitioned into a plurality of storage device segments. A storage device segment reliability level may be defined for the plurality of storage device segments based upon, at least in part, the storage device reliability level of the plurality of storage devices. A subset of the plurality of storage device segments may be combined, thus defining a storage device segment extent. A RAID level for the storage device segment extent may be selected based upon, at least in part, the storage device segment reliability level of each storage device segment of the storage device segment extent.

Abstract: In accordance with embodiments of the present disclosure, an information handling system may include a processor, a memory communicatively coupled to the processor and comprising a plurality of non-volatile memories, and a failure analysis module comprising a program of instructions, the failure analysis module configured to, when read and executed by the processor, set a predictive failure threshold for each of the plurality of non-volatile memories based at least on functional parameters of such non-volatile memory, and adapt the predictive failure threshold for each of the plurality of non-volatile memories based at least on health status parameters of such non-volatile memory.

Abstract: The invention relates to a method for monitoring at least two redundant sensors, which are in particular arranged in a chemical plant or an aircraft, comprising providing a first sensor signal of a first sensor, the first sensor signal comprising at least one measured value, providing at least one further sensor signal from a further sensor, the further sensor signal comprising at least one further measured value, generating a first analysis signal from the first sensor signal, generating at least one further analysis signal from the further sensor signal, determining at least one relationship between the first sensor signal and the further sensor signal at least in dependence on the first analysis signal and the further analysis signal over a time horizon, comparing the relationship with at least one admissible range, and, depending on the result of the comparison, determining whether at least one sensor of the two redundant sensors is faulty.

Abstract: A processor includes a front end, an execution unit, a retirement stage, a counter, and a performance monitoring unit. The front end includes logic to receive an event instruction to enable supervision of a front end event that will delay execution of instructions. The execution unit includes logic to set a register with parameters for supervision of the front end event. The front end further includes logic to receive a candidate instruction and match the candidate instruction to the front end event. The counter includes logic to generate the front end event upon retirement of the candidate instruction.

Abstract: In an approach to limiting container CPU usage based on network traffic, a packet CPU usage for each packet type of one or more packet types is determined. A network CPU usage is calculated for a specific container based on the network CPU usage for each packet type. A container process CPU usage and a total container CPU usage are calculated for the specific container, where the total container CPU usage is the sum of the network CPU usage and the container process CPU usage. Responsive to determining that the total container CPU usage exceeds a threshold, the container CPU consumption quota and the container network bandwidth setting for the specific container are adjusted to reduce the total container CPU usage, using a set of pre-configured parameters.

Abstract: Embodiments provide a computer-executable method for programmatically generating one or more survey queries. The method includes accessing information on a commercial entity or object. The method also includes, based on the accessed information, determining an attribute descriptor associated with the attribute. The method further includes programmatically generating a survey query indicating the attribute descriptor. The method further includes transmitting one or more computer-executable instructions to a computing device to cause a visual display device to render a user interface, the user interface displaying the survey query and enabling user input in response to the survey query.

Abstract: A control device of an internal combustion engine includes a parameter acquisition unit that acquires a plurality of input parameters, a calculation unit that calculates at least one output parameter using a neural network model, and a controller that controls the internal combustion engine. The neural network model includes a plurality of neural network units and an output layer. Each of the neural network units includes one input layer and at least one intermediate layer. The neural network model inputs different combinations of input parameters selected from the input parameters to each of the input layers of the neural network units such that a total number of input parameters to be input to the neural network units is larger than the number of the input parameters.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to generate reference signatures from streaming media through the collection of metadata, generation of audio signatures, and association of the metadata with the generated audio signatures. The disclosure consists of a media monitor that collects metadata and generates audio signatures at a household and a central processing facility that generates reference signatures therefrom.

Abstract: Systems, computer-implemented methods, and computer program products to facilitate discovery of an inexplicit link between a change and an incident in a computing environment are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise an analysis component that determines a defined link strength corresponding to links between change data and incident data in a computing environment. The computer executable components further comprise an extraction component that employs a model to identify an inexplicit link between the change data and the incident data based on the defined link strength.

Abstract: A method for performing high availability management of an all flash array (AFA) server and the AFA server operating according to the method are provided. The method may include: utilizing a monitor and poller module among multiple program modules running on any node of multiple nodes of the AFA server to monitor multiple types of resources of the AFA server, wherein the multiple program modules running on the any node comprise a hardware manager, and the hardware manager is configured to manage multiple hardware components in a hardware layer of the any node, to allow at least one portion of associated monitoring results regarding the multiple types of resources to be obtained through the hardware manager; and controlling the any node to select suitable candidate operation from multiple candidate operations respectively corresponding to the multiple monitored-information types according to at least one predetermined table to perform the suitable candidate operation.

Abstract: This invention provides a method for providing trusted display to security sensitive applications on untrusted computing platforms. This invention has a minimal trusted code base and maintains full compatibility with the computing platforms, including their software and hardware. The core of the invention is a GPU separation kernel that (1) defines different types of GPU objects, (2) mediates access to security-sensitive GPU objects, and (3) emulates accesses to security-sensitive GPU objects whenever required by computing platform compatibility.

Abstract: Example embodiments of the present invention relate to methods, systems, and a computer program product for managing a virtual datacenter. The method includes tracking configuration metadata for a virtual datacenter operating at a first site and simulating the virtual datacenter at a second site according to the tracked virtual datacenter configuration metadata. An analysis then may be performed on operation of the simulated virtual datacenter at the second site.