Abstract: An analysis system includes a control module generates data gathering parameters and data analysis parameters based on one or more inputs regarding an evaluation of a system aspect under test of a system, a data input module receives system gathered data regarding the system aspect under test to produce gathered data, and a data analysis module configured to generate the evaluation of the system aspect under test based on the data analysis parameters and the gathered data One or more databases store one or more of the gathered data, the data analysis parameters, and the evaluation of the system aspect under test and one or more data extraction modules interact with the system aspect under test to extract data from the system aspect under test in accordance with a respective portion of the data gathering parameters to produce the system gathered data and provide the system gathered data.

Abstract: Embodiments of the present disclosure provide an operation and maintenance system and method. The operation and maintenance system comprises a plurality of interconnected modules including: a data acquisition module, a data storage module, an exception and fault labeling module, an automatic model training and assessment module, an operation and maintenance management and task execution module, and a result checking module.

Abstract: An electronic device including a processor and a sensor may be provided. The processor obtains a first degree of degradation of a first core based on a first parameter value associated with a lifetime of the first core and a first operating level associated with an operation of the first core. The processor obtains a second degree of degradation of a second core based on a second parameter value associated with a lifetime of the second core and a second operating level associated with an operation of the second core. The processor schedules a task of the first core and the second core based on the first degree of degradation and the second degree of degradation. The sensor provides the first parameter value and the first operating level to the first core and the second parameter value and the second operating level to the second core.

Abstract: A method of logging thread parallelism data include executing a plurality of threads at a multicore processor associated with an operating system to perform symmetrical multiprocessing. The method also includes tracking, at a logging subsystem of the operating system, an accumulated runtime associated with each thread combination of the plurality of threads during execution of the plurality of threads. The accumulated runtime of a particular thread combination increases while the particular thread combination is running on the multicore processor in parallel. The method also include generating, at the logging subsystem, logging data indicating the accumulated runtime for each thread combination. The method further includes outputting the logging data. The logging data is usable to increase thread parallelism at the multicore processor.

Abstract: Methods and system are provided for determining a system capacity. The system capacity may be determined by performing one or more capacity tests. The one or more capacity tests may produce capacity test results.

Abstract: An aspect of the present disclosure provides a relevance ranking system for events identified by performance management systems. In one embodiment, a system receives, from one or more performance management systems, events associated with performance metrics and determines, based on the received events, a corresponding relevance score for each performance metric. The system generates a ranking list of the received events based on the corresponding relevance scores (determined for the performance metrics). The system then provides the ranking list of events to a user (such as an administrator). According to another aspect, the system (noted above) performs the steps of receiving, determining, and generating for each time interval of a set of time intervals.

Abstract: Systems and methods are described for operating a hybrid computing system using cluster contraction for converting large, dense input to reduced input that can be easily mapped into a quantum processor. The reduced input represents the global structure of the problem. Techniques involve partitioning the input variables into clusters and contracting each cluster. The input variables can be partitioned using an Unweighted Pair Group Method with Arithmetic Mean algorithm. The quantum processor returns samples based on the reduced input and the samples are expanded to correspond to the original input.

Abstract: An apparatus to collect firmware measurement data at a computing system is disclosed. The apparatus includes a plurality of agents, each including a non-volatile memory storing firmware executed to perform a function associated with the agent, verification logic to generate measurement data by verifying the integrity of the firmware and a register to store the measurement data, and a processor to execute an instruction to collect firmware measurement data from each of the plurality of agents.

Abstract: A detecting device (10) acquires information related to communication by an IoT device. The detecting device (10) inputs data representing a feature of the information related to the communication to a generative model which generates output data on the basis of a latent variable which is a random variable according to a mixed Gaussian distribution and input data, and calculates the output data. The detecting device (10) calculates an anomaly score on the basis of the output data and detects an anomaly in the IoT device when the anomaly score exceeds a threshold value.

Abstract: A system to provide increased visibility and insight into unexpected usage patterns for electronic devices is described. The utilization analysis system applies a utilization model to device utilization information. The utilization model is also used to determine one or more device usage patterns for the electronic device. These device usage patterns are used to determine an unexpected device utilization where the system responds to the unexpected device utilization with several hardware and software solution proposals to prevent damage to the electronic device and/or enhance the design and development of the electronic device.

Abstract: Embodiments disclosed include methods and systems that adaptively, in real-time, evaluate data center performance, assess data center efficiency, data center sustainability, data center availability, compute performance, storage performance and provide data center customers with an overall data center performance rating, presented as a Total Resource Utilization Efficiency or TRUE score. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods. Other embodiments of the methods or systems include addition of newly defined metrics as categories or sub-categories to be used to calculate data center TRUE score.

Abstract: The present disclosure discloses a method and apparatus for testing a stress based on a cloud service, and relates to the field of cloud computing technology, and further to the field of cloud operation and maintenance technology. A particular implementation comprises: acquiring, based on first stress test information of a business system in a cloud service, a number of expected stress test nodes corresponding to the business system; creating edge computing nodes, a number of the edge computing nodes being identical to the number of the expected stress test nodes; and performing a stress test on the business system by using the edge computing nodes, to acquire second stress test information of the business system.

Abstract: A deployment manager executing in a distributed computing environment generates a user behavior analytics (UBA) deployment to process structured event data. The deployment manager configures a streaming cluster to perform streaming processing on real-time data and configures a batch cluster to perform batch processing on aggregated data. A configuration manager executing in the distributed computing environment interoperates with the deployment manager to update the UBA deployment with user-provided code and configurations that define streaming and batch models, among other things. In this manner, the deployment manager provides a scalable UBA deployment that can be customized, via the configuration manager, by a user.

Abstract: Techniques for multi-domain systems integration and evaluation are disclosed, including: obtaining criteria associated with a strategic objective; determining that a first system, operating in a first operating domain, is only partially capable of satisfying a first criterion in the criteria; determining that a second system, operating in a second operating domain that is different from the first operating domain, is capable of augmenting the first system with respect to satisfying the first criterion; responsive to determining that the second system is capable of augmenting the first system with respect to satisfying the first criterion, modeling a multi-domain system including at least a first component from the first system and at least a second component from the second system; and generating a performance metric that objectively evaluates capabilities of the multi-domain system against the criteria associated with the strategic objective.

Abstract: An apparatus and method are provided for processing instructions. The apparatus has execution circuitry for executing instructions, where each instruction requires an associated operation to be performed using one or more source operand values in order to produce a result value. Issue circuitry is used to maintain a record of pending instructions awaiting execution by the execution circuitry, and prediction circuitry is used to produce a predicted source operand value for a chosen pending instruction. Optimisation circuitry is then arranged to detect an optimisation condition for the chosen pending instruction when the predicted source operand value is such that, having regard to the associated operation for the chosen pending instruction, the result value is known without performing the associated operation.

Abstract: An approach is provided in which the approach captures an image of a component rack that includes a set of hardware components that are part of a hyperconverged system. The approach discovers the set of hardware components on a computer network during a domain-specific discovery process, and verifies that each one of the set of hardware components captured in the image matches one of the discovered set of hardware components. The approach monitors a status of the set of hardware components in response to verifying that each one of the set of hardware components captured in the image matches one of the discovered set of hardware components.

Abstract: A disclosed transmitter for wireless communication includes multiple transmitting antennas, a symbol mapper for mapping an input block including multiple binary bits and representing information to be transmitted to a symbol representing an ordered plurality of complex numbers, a space-time encoder for applying an encoding operator to the symbol to produce a vectorized space-time codeword defining electrical signals to be transmitted by the transmitter, the encoding operator being dependent on a set of predefined stabilizer generators, and circuitry to collectively transmit, by the antennas to multiple receiving antennas of a receiver over a wireless transmission channel, the electrical signals defined by the vectorized space-time codeword. The receiver includes a space-time decoder for recovering the symbol from the electrical signals transmitted by the transmitter using a decoding operation that is based on maximum likelihood inference, and a symbol de-mapper for recovering the input block from the symbol.

Abstract: Aspects of the present disclosure involve systems and methods for improving the performance of a telecommunications network by monitoring the performance of one or more storage drives. Operational data is received from a plurality of storage drives of a storage server of a telecommunications network. A plurality of operational coefficients for each of the plurality of storage drives is derived based on the operational data, and a cluster plot is created from the plurality of operational coefficients for each of the plurality of storage drives. A distance is calculated between a subset of operational coefficients of the plurality of operational coefficients of the cluster plot, and a remedial action is initiated on a storage drive of the plurality of storage drives when a calculated distance of an operational coefficient associated with the storage drive exceeds a distance value from a cluster of the cluster plot.

Abstract: Example predictive wireless feedback control systems disclosed herein include a receiver to receive measurements of a controlled system via a first wireless link. Disclosed example systems also include an observer to output estimated values of states of the controlled system based on a state space model that is updated based on the measurements. Disclosed example system further include a predictor to predict future values of the states of the controlled system based on the estimated values of the states, a first latency of the first wireless link and an upper limit of a second latency associated with a second wireless link that is to communicate values of a control signal to an actuator associated with the controlled system. In disclosed examples, the predictor is to output the predicted future values of the states to a controller that is to determine the control signal.

Abstract: One or more non-transitory computer readable media containing program instructions that, when executed by one or more processors, cause the one or more processors to perform operations: generating a database of interconnected smart entities, the smart entities including object entities representing each of the plurality of physical devices and data entities representing data generated by the devices, the smart entities being interconnected by relational objects indicating relationships between the object entities and the data entities; receiving data from a first device of the plurality of physical devices; determining a second device from a relational object for the first device based on the received data; and modifying a data entity connected to an object entity of the second device within the database of smart entities based on the received data for the first device.

Abstract: Aspects relate to system and methods for determining a user specific mission operational performance, using machine-learning processes.

Abstract: A storage device is provided to comprise a memory device for storing data, a cache memory device including a first cache memory configured to cache certain data stored in the memory device and a second cache memory configured to store data evicted from the first cache memory, and a memory controller configured to receive a read request for first data from a host, evict second data from the first cache memory based on a reuse distance of the second data, store the second data in the second cache memory, load the first data to the first cache memory, and transmit the first data to the host.

Abstract: Monitoring a set of virtual users during performance testing and reporting virtual user operations data to ensure an ongoing and constant transactions per second load and providing test result data with evidence of constant transactions per second (TPS) during the test. Generating and executing performance tests under constant TPS includes restarting virtual users that are terminated during the performance tests.

Abstract: In some examples, a method of operating a circuit may comprise performing a circuit function under normal conditions, performing the circuit function under aggravated conditions, predicting a potential future problem with the circuit function under the normal conditions based on an output of the circuit function under the aggravated conditions, and outputting a predictive alert based on predicting the potential future problem.

Abstract: Described herein are systems, methods, and software to enhance the management and deployment of data processing clusters in a computing environment. In one example, a management system may monitor data processing efficiency information for a cluster and determine when the efficiency meets efficiency criteria. When the efficiency criteria are met, the management system may identify a new configuration for the cluster and initiate an operation to implement the new configuration for the cluster.

Abstract: Systems and methods for cache optimization are disclosed. A request for a user interface is received from a first user device. The request includes a user key. An interface key corresponding to an interface template of the requested user interface is generated from the user key. The interface template of the requested user interface is loaded. The interface template includes one or more edge side include (ESI) identifiers in the interface template. An element key corresponding to a first ESI element associated with a first of the one or more ESI identifiers is generated from the user key. The first ESI element is loaded and positioned at a location within the interface template identified by the first of the one or more ESI identifiers. A complete user interface is provided to the first user device. The complete user interface includes the interface template having the first ESI element positioned therein.

Abstract: Load testing a service having a plurality of different states is provided. A multitude of simulated users accessing the service are divided into a plurality of cohorts. Simulated users within a given cohort share a similar personality type. A load test of the service is performed by applying a set of service requests from each respective cohort to the service. In response to a percentage of simulated users of each cohort encountering a particular state in the service, a user response is determined for the percentage of simulated users within each cohort at that particular state based on a probabilistic user behavior model corresponding to a personality type of each cohort such that user responses at that particular state are distributed in accordance with the probabilistic user behavior model. Distributed user responses at that particular state are applied to the load test in accordance with the probabilistic user behavior model.

Abstract: Systems and methods are described for performing adaptive thresholding on key performance indicator (KPI) values using an online machine learning algorithm as the KPI values or the data from which the KPI values are derived is being ingested. For example, the system can identify outliers in a moving window of KPI values. To implement the adaptive thresholding, the system may identify seasonality and/or trend components in historical KPI values. When a new KPI value is obtained, the system may remove the identified seasonality and/or trend components from the KPI value, and determine whether the modified KPI value is an outlier using sketches or quantiles. The system can then repeat this process for each subsequently received KPI value.

Abstract: Systems, methods, and computer-readable media for providing physical rewards from disbursed networked dispensers are disclosed. The systems and methods may involve at least one processor configured to: maintain and cause to be displayed a workflow table having rows, columns and cells; track a workflow milestone via a designated cell configured to maintain data indicating that the workflow milestone is reached; access a data structure storing a rule containing a condition associated with the designated cell and a conditional trigger associated with at least one dispenser; receive an input via the designated cell; compare the input with the condition to determine a match; and activate the conditional trigger to cause at least one dispensing signal to be transmitted over a network to the at least one dispenser to cause the at least one dispenser to dispense a physical item as a result of the milestone being reached.

Abstract: In one embodiment, a software agent profiler process attaches to an application and a primary instrumentation interface for the application, and discovers one or more software agents associated with the application. The software agent profiler process may then launch the one or more software agents within an encapsulated container environment of the software agent profiler process by configuring each of the one or more software agents, respectively, to point to a proxy instrumentation interface of the software agent profiler process instead of the primary instrumentation interface for the application. As such, the software agent profiler process may receive calls from the one or more software agents on the proxy instrumentation interface of the software agent profiler process, and can manage the calls from the one or more application agents prior to the calls being passed to the primary instrumentation interface for the application.

Abstract: A data-driven approach to network performance diagnosis and root-cause analysis is presented. By collecting and aggregating data attribute values across multiple components of a content delivery system and comparing against baselines for points of inspection, network performance diagnosis and root-cause analysis may be prioritized based on impact on content delivery. Recommended courses of action may be determined and provided based on the tracked network performance analysis at diagnosis points.

Abstract: Optimizing backups for a data protection system by determining a size of a dataset to be saved in each backup operation and an available bandwidth in each transfer window of transfer windows for data transfers between a source and destination. An order of the backup operations is defined based on first ordering the backups based on decreasing dataset size and second ordering the transfer windows in order of decreasing bandwidth, and matching the backups to the transfer windows in accordance with these orderings. A dynamic window sizing process determines an initial change between the minimum and maximum bandwidth utilization over a period of time and then iteratively split and consolidate the time blocks until optimal utilization over the time period is reached.

Abstract: The present disclosure discloses a method and apparatus of monitoring an interface performance of a distributed application, a device and a storage medium, which relates to a field of computer technology, in particular to a field of cloud platform. The method includes: in case of detecting a caller request for calling an interface of the distributed application, obtaining a performance data of the interface for responding the caller request; updating a performance data distribution characteristic of the interface according to the performance data of the interface for responding the caller request, so as to obtain an updated performance data distribution characteristic; and monitoring the interface performance of the distributed application, according to the updated performance data distribution characteristic of the interface.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for self-optimization of computing environments. In some implementations, different combinations of settings used by one or more server environments are determined. Results achieved by the one or more server environments are monitored when using the different combinations of settings. Based on the monitored results, one or more performance measures are generated that correspond to each of the different combinations of settings. An updated set of settings are selected for a particular server environment based on the performance measures. The selected settings are provided for the particular server environment.

Abstract: A CPU having a plurality of cores is configured by determining a number of cores required for operation of the CPU. Each respective core is tested, and a performance parameter of the respective core is determined based on the test. The respective core is then classified for suitability to perform a set of functions based on the performance parameter of the respective core. If at least the number of cores required for operation of the CPU are classified for suitability to perform the set of functions, a subset of suitable cores is defined, the subset including cores that are classified for the set of functions and at least the number of cores required for operation of the CPU. The required number of cores from among the subset of cores are then enabled.

Abstract: Techniques are provided for implementing multi-track audio analysis. In some instances, a plurality of audio tracks are received and combined into a single audio file. A collection of audio file characteristics are extracted from the single audio file. In some examples, the collection of audio file characteristics are associated with of the plurality of audio tracks and the single audio file. Audio characteristic edits are received for revising the collection of audio file characteristics. Metadata associated with each of the plurality of audio tracks and for the single audio file are updated based at least in part on the audio characteristic edits.

Abstract: A computer-implemented method for determining influence of applications on system performance includes collecting, by a processor, for several applications that are executing on a computing system, respective instrumentation data during multiple time-segments. The method further includes determining, for each of the applications, a performance value and a robustness value for each of the time-segments based on the respective instrumentation data. Further, using the performance value and robustness value for each time-segment, multiple health-waveforms are generated, where a health-waveform is generated for each respective application. The method further includes determining, by the processor, an influence-factor of a first application on a second application, the first application and the second application are executing on the computing system.

Abstract: Monitoring and enhancing performance of containers using a calibration technique is implemented using a computer. Performance of a new container as part of an application running on the computer is checked by comparing a current performance of the new container with baseline data corresponding to the new container. The baseline data is derived from a calibration container corresponding to the new container. The new container is categorized in a category of performance based on the checking of the performance of the new container. An alert can be sent to a device of an administrator regarding the new container meeting a threshold of performance, in response to the new container meeting the threshold of performance. The alert can be sent to the device of the administrator for the administrator to initiate an action pertaining to the new container in response to receiving the alert.

Abstract: A network device includes a memory and one or more processors in communication with the memory. The one or more processors are configured to configure a proxy server to forward a request for data from a client device to a data server and to forward, from the data server to the client device, a response message that is responsive to the request for data. The one or more processors are further configured to receive an indication of a set of header fields for the response message that indicates a first time specifying when the data server received the request for data and a second time specifying when the response message was sent by the data server and generate a metric for a performance of the data server based on the first time and the second time.

Abstract: A method and a device for analyzing a consumption of resources in a computing infrastructure to predict a resource consumption anomaly on a computing device. The method includes determining a plurality of resource consumption modeling functions; determining a correlation between the resource consumption modeling functions; measuring a resource consumption by a measurement of a consumption value of a first resource; and predicting the resource consumption of the computing infrastructure. The predicting includes a calculation of a value of future consumption of a resource to be predicted from the consumption value of the first resource and from a previously calculated correlation between modeling functions.

Abstract: In one embodiment, a method selects a percentage of a plurality hosts that are coupled together via a network fabric and calculates a number of workloads needed for the percentage of hosts based on a benchmark test to run. A plurality of data compute nodes are configured on one or more host pairs in the percentage of the plurality of hosts to send and receive the number of workloads through the network fabric to perform the benchmark test. A set of measurements is received for sending and receiving the workloads through the network fabric using the plurality of data compute nodes. The method increases the percentage of the plurality of hosts until the set of measurements fails a criteria or the percentage of the plurality of hosts is all of the plurality of hosts.

Abstract: A computing system is configured to analyze both measurement data and indicator data as big data aggregated in measurement database and indicator database by deep learning for each lot of a part or for each lot of a finished product and a part pre-associated with each other, and also for each consolidation target between bases subordinate to the same start point corresponding to identification information that specifies a business user of the computing system. Analysis target layers by the deep learning are a three-layer serial hierarchical structure containing a production condition layer and an environment condition layer as a start point for analysis of a part layer, or a four-layer serial hierarchical structure containing a part layer, a production condition layer, and an environment condition layer as a start point for analysis of a finished product layer.

Abstract: Methods, systems, and devices for techniques for configuring a transaction funnel are described. A server may receive, from a provider, a first set of rules for providing a product or service of the provider. The server may transmit, to an entity of the product or service, the first set of rules received from the provider. The server may receive, from the entity, a second set of rules for providing the product or service, where the second set of rules may be based on the first set of rules. Using the configuration techniques, the server may generate a transaction funnel associated with providing the product or service.

Abstract: A data acquisition system for dielectric analysis measurements, including a sensor interface configured to connect to one or more sensors located within an active machining zone of an industrial manufacturing machine, a module processor coupled to the sensor interface and configured to receive measurement values from one or more sensors connected to the sensor interface, a cloud interface coupled to the module processor, and a machine interface coupled to the module processor. The measurement values indicate physical properties of workpieces processed in the active machining zone of an industrial manufacturing machine. The cloud interface is configured to connect to cloud-based resources, and the machine interface is configured to connect to a controller of the industrial manufacturing machine.

Abstract: A computer-implemented method, which enables the data to be clustered without being required to perform any distance calculations among the points of the dataset, includes assigning points of a dataset to cells of a cellular automaton; assigning each cell, having a data point assigned, a distinct state value and a constant temperature value; and assigning all cells, to which a data point is not assigned, a unique state value different from the state values utilized for cells having a data point and to a temperature lower than the constant temperature value; selecting a cell in the cellular automaton randomly; calculating the average temperature of the selected cell and its neighbor cells; setting the temperature of the cells having no data point, as the average temperature; if a neighbor cell temperature is above the predetermined threshold value, moving this neighbor cell to the state of the selected cell.

Abstract: In an embodiment, a processor includes processing cores, and a central control unit to: concurrently execute an outer control loop and an inner control loop, wherein the outer control loop is to monitor the processor as a whole, and wherein the inner control loop is to monitor a first processing core included in the processor; determine, based on the outer control loop, a first control action for the first processing core included in the processor; determine, based on the inner control loop, a second control action for the first processing core included in the processor; based on a comparison of the first control action and the second control action, select one of the first control action and the second control action as a selected control action; and apply the selected control action to the first processing core. Other embodiments are described and claimed.

Abstract: Techniques for determining replication modes may include: issuing, while unsolicited data transfer mode is enabled for a first link, first write operations over the first link; issuing, while unsolicited data transfer mode is disabled for the first link, second write operations over the first link; determining a first performance metric for the first link in accordance with the first write operations; determining a second performance metric for the first link in accordance with the second write operations; and determining, in accordance with the first and second performance metrics whether to enable or disable unsolicited data transfer mode for the first link for a first time period. The first and second performance metrics may be response times. Unsolicited data transfer mode, when enabled, allows write data payload to be sent to a target without receiving an acknowledgement regarding receipt of a write command block for the write operation from the target.

Abstract: Techniques for generating change notifications associated with applications based on application logs are disclosed. In one embodiment, a system may include a log analyzer to receive application logs generated by the applications running in a computing environment and analyze the received application logs to parse information about the applications. Further, the system may include a change detection unit communicatively coupled to the log analyzer to generate a change notification indicating that a change has been occurred to an application running on a compute node in the computing environment using the parsed information and send the change notification indicating the changed application to a subscriber.

Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for managing a storage system. The method includes: if it is determined based on current values of a plurality of attribute parameters of a storage device in a storage system that the storage device will have a fault, determining whether the fault of the storage device will not occur again based on reference values of attribute parameters in a first set in the plurality of attribute parameters and current values of attribute parameters in a second set in the plurality of attribute parameters. The method further includes: if it is determined that the fault of the storage device will not occur again, determining a cause of the fault based on the attribute parameters in the first set. The embodiments of the present disclosure can analyze a cause of a fault of a storage device, thereby avoiding the misjudgment of a storage device having no internal fault as a storage device having an internal fault.

Abstract: In disclosed techniques, datacenter power management uses AC and DC power sources. An AC power distribution topology within a datacenter provides one or more AC power sources to computing devices. A DC power distribution topology within the datacenter provides one or more DC power sources to computing devices. An uninterruptible power supply (UPS) is provisioned to a rack of computing devices, wherein the UPS is capable of receiving the one or more AC power sources using the AC power distribution topology and the one or more DC power sources using the DC power distribution topology. The one or more DC power sources are evaluated for energizing the DC power distribution topology. The one or more DC power sources are connected to the UPS which is provisioned to the rack of computing devices, based on the evaluating and a datacenter power requirement.