Abstract: Recovery processing is provided for management components of an Information Technology (IT) environment. The recovery processing recovers the components, as well as performs one or more tasks that were being performed by the components prior to recovery.

Abstract: This disclosure describes methods, systems and software that can be used to calculate the estimated mean time to data loss for a particular configuration of a disk group. For example, a system can be used to evaluate a plurality of configurations, and/or to select (and/or allow a user to select) an optimal configuration of the disk group, based, in some cases, on the relative estimated mean times to data loss of the various configurations. This can allow, if desired, the configuration of the disk group to minimize the likelihood of data loss in the disk group.

Abstract: A first module calculates a failure occurrence risk index of each data storage area address. A second module calculates a power saving index of each data storage area address. A third module calculates an access speed index per unit data volume necessary to access each data storage area address. A fourth module generates a distribution table that represents the failure occurrence risk index, the power saving index, and the access speed index for each candidate address, with respect to data to be distributed. A fifth module selects a candidate address in the distribution table such that the power saving index and the access speed index meet restricting conditions and the failure occurrence risk index is minimized, and distributes the data to the candidate address.

Abstract: A computer implemented method, computer program product and system for monitoring a plurality of hardware or software system resources for identifying hidden trends in the behavior of the system resources, includes: collecting metrics of at least one system resource indicative of the behavior of at least one system resource; for each of the at least one system resource, determining a spectrum representative of a time-based signal of the collected metrics; performing a wavelet transform on each of the at least one spectrum; and analyzing the result of the wavelet transform to identify possible linear trends in the behavior of the at least one system resource.

Abstract: Embodiments of the disclosure relate to a method and system for measuring preventability metric of an application. The preventability metric quantifies the extent to which bugs and failures, and the causes for failures are diagnosed in the application. Also, the extent to which appropriate preventive or corrective activities are deployed before deployment of the application is provided. Further, a framework to monitor and control the preventability metric systematically is disclosed. The methodology is to obtain the efficiency of the preventive techniques used on the application, use the obtained efficiency measures to arrive at a preventability metric that quantifies the preventability of failures of the application.

Abstract: A method of predicting disk drive failure at a central processing facility using an evolving drive failure prediction algorithm (DFPA) is disclosed. A set of quality metric values are transmitted from each of a plurality of remote disk drives to the central processing facility. The DFPA is executed at the central processing facility in response to the quality metric values to detect an impending failure of at least one of the remote disk drives. The DFPA is evolved at the central processing facility in response to a reference data base of quality metric values and a corresponding failure indicator. The processes is repeated so as to improve the accuracy of the DFPA over time.

Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in database services. In an embodiment, a computer system monitors various health indicators for multiple nodes in a database cluster. The computer system accesses stored health indicators that provide a health history for the database cluster nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: A performance monitoring technique provides task-switch immune operation without requiring storage and retrieval of the performance monitor state when a task switch occurs and provides accurate performance monitoring information. When a hypervisor signals that a task is being resumed and the application privilege level has been entered, it provides an indication, which starts a delay timer. The delay timer is resettable in case a predetermined time period has not elapsed when the next task switch occurs. After the delay timer expires, analysis of the performance monitor measurements is resumed, which prevents an initial state, a state due to execution of the operating system or hypervisor, or a state remaining from a previous task from corrupting the performance monitoring results. The performance monitor may be or include an execution trace unit that collects branch information in a current program execution trace.

Abstract: Embodiments pertain generally to a method of providing a remote monitoring subscription service. The method includes receiving client activity data from at least one of a client virtual machine and a physical machine supporting the client virtual machine at a site of a customer and comparing the client activity data against a set of performance guidelines. The method also includes determining a recommended action in response to the client activity data not falling within the set of performance guidelines and forwarding the recommended action to the customer.

Abstract: A method for a computer including a processor that is capable of counting invalidation of translation lookaside buffers and generating an interrupt at the occurrence of the invalidation, the invalidation being performed by an operating system upon switching between application programs, includes acquiring identification information of application programs from the operating system and storing the identification information as a first list; detecting an interrupt generated from the processor at the occurrence of switching from a first application program to a second application program; and when the interrupt is detected, acquiring the identification information of the first and second application programs from the operating system or the mechanism and comparing the acquired identification information with the first list to determine whether either of the first and second application programs is a program that has been created or disappeared.

Abstract: A printer monitoring apparatus includes a setting unit configured to set a display mode of a warning or an error related to a peripheral device, a determination unit configured to determine whether the warning or the error has previously occurred, a display unit configured to display the warning or the error in a case where the warning or the error has previously occurred, and a processing unit configured to continue a process or cancel a process according to the warning or the error based on whether the warning or the error has previously occurred.

Abstract: A trouble prediction apparatus includes a trouble-occurred device information storage unit that stores therein trouble occurrence information of trouble-occurred devices in which a trouble has occurred out of a plurality of management target devices; a calculating unit that calculates a trouble occurrence probability based on the trouble occurrence information; and a predicting unit that predicts a trouble of a prediction target device out of the management target devices by referring to the trouble occurrence probability.

Abstract: In an embodiment, a data processing method comprises: a computer obtaining occurrence data representing one or more performance measurements collected for a network device and associated with one or more data metrics; monitoring the occurrence data; determining one or more current trends that are reflected in the occurrence data; determining one or more predicted trends for the network device; determining, based on the predicted trends, one or more future events that are predicted to occur at the network device at a future time; determining, by applying a site policy to the one or more future events, one or more preventive actions for the network device to prevent occurrence of the one or more of the future events.

Abstract: A computer-implemented reservoir prediction system, method, and software are provided for failure prediction for artificial lift systems, such as sucker rod pump systems. The method includes a production well associated with an artificial lift system and data indicative of an operational status of the artificial lift system. One or more features are extracted from the artificial lift system data. Data mining is applied to the one or more features to determine whether the artificial lift system is predicted to fail within a given time period. An alert is output indicative of impending artificial lift system failures.

Abstract: A method of isolating relevant components associated with a performance problem. The method comprises creating a static model of a system under test, including determining relationships between components in a middleware system. The method also comprises creating a dynamic problem tree by applying the static model to the system at runtime. The method further comprises identifying a link probability for each relationship in the dynamic problem tree; and traversing the dynamic problem tree to detect redundant components. A component is redundant if it has a link probability with its downstream component greater than a pre-determined threshold value. The method also comprises removing redundant components from the dynamic problem tree; and returning a set of components which are potential components to be analyzed further to determine the root causes of the performance problem.

Abstract: The present embodiments disclose a method and an associated computer program product for determining the quality of an information technology (IT) system including a plurality of hardware units and software modules. A total score value for the IT system is calculated from different score values ascertained independently of one another. The different score values are measures for deviations of the quality of the hardware units or the software modules from first predefinable target values. The total score value is a measure of a deviation of the quality of the IT system from a second predefinable target value.

Abstract: Technologies are described herein for differentiating normal operation of an application program from error conditions to predict, diagnose, and recover from application failures. Access to resources by the application program is monitored, and resource access events are logged. Resource access patterns are established from the logged resource access events utilizing computer pattern recognition techniques. If subsequent access to resources by the application program deviates from the established patterns, then a user and/or administrator of the application program is notified of a potential error condition based on the detected deviation. In addition, sequences of resource access events that deviate from the established resources access patterns are correlated with an error condition based on a temporal proximity to the time of occurrence of the error to provide diagnostic information regarding the error.

Abstract: Disclosed is a method and apparatus for realizing an effective service adaptation in consideration of delay factors possibly generated in combining (or compositing) already existing Web services in constituting a composite Web service. A failure or delay in executing a Web service is predicted in consideration of features (or factors) of QoS of Web services constituting a composite Web service, and a substitute Web service is executed or a speculative execution is performed to thus stably and quickly constitute a composite Web service.

Abstract: Included are embodiments of a method for detecting errors in a set top terminal (STT). At least one embodiment of a method includes receiving error data related to at least one error that occurred in at least one STT and comparing the received error data to at least one signature file, the at least one signature file including a pattern related to at least one documented error. Additional embodiments of the method may also include in response to determining that the received error data does not match the pattern related to at least one documented error, creating a new signature file, the new signature file including at least one pattern associated with the received error data.

Abstract: A distributed messaging system and method allows servers in a network to share data, such as network status data associated with all of the servers in the network. In one embodiment, the distributed messaging system and method may be used in element management system (EMS) servers in a distributed network management system (NMS). The servers in the network share the data in a distributed manner by transmitting messages including the network status data, for example, using a star/broadcast method or a circular message queue (CMQ) method.

Abstract: Various embodiments of the present invention provide systems and methods for managing solid state drives. As an example, a storage system is described that include at least a first flash memory block and a second flash memory block, and a control circuit. The first flash memory block and the second flash memory block are addressable in the storage system. The control circuit is operable to identify the first flash memory block as partially failed, receive a write request directed to the first flash memory block; and direct the write request to the second flash memory block.

Abstract: Methods and apparatus are provided for determining the fault diagnosability of a health monitoring software application for a complex system. The method includes extracting data from the software application containing a relationship between one or more failure modes of the complex system and one or more evidence items of the complex system, the a priori probabilities of each failure mode occurring, and the a priori probability of each evidence item occurring. The method also includes creating one or more matrices relating the one or more FMs to the one or more evidence items. The method further includes analyzing the one or more matrices and the a priori probabilities to determine the diagnosability of each FM.

Abstract: In one embodiment, a processor comprises a circuit coupled to receive an indication of a memory operation to be executed in the processor. The circuit is configured to predict whether or not the memory operation is misaligned. A number of accesses performed by the processor to execute the memory operation is dependent on whether or not the circuit predicts the memory operation as misaligned. In another embodiment, a misalignment predictor is coupled to receive an indication of a memory operation, and comprises a memory and a control circuit coupled to the memory. The memory is configured to store a plurality of indications of memory operations previously detected as misaligned during execution in a processor. The control circuit is configured to predict whether or not a memory operation is misaligned responsive to a comparison of the received indication and the plurality of indications stored in the memory.

Abstract: One embodiment provides a method for scalable predictive failure analysis. Embodiments of the method may include gathering memory information for memory on a user computer system having at least one processor. Further, the method includes selecting one or more memory-related parameters. Further still, the method includes calculating based on the gathering and the selecting, a single bit error value for the scalable predictive failure analysis through calculations for each of the one or more memory-related parameters that utilize the memory information. Yet further, the method includes setting, based on the calculating, the single bit error value for the user computer system.

Abstract: An incident predictor system is described herein for predicting impactful incidents in which server computer system operations fail or perform poorly. According to one embodiment of the invention, the incident prediction system trains a generalized linear model (GLM) to predict when a system health indicator will reach a level that represents an incident for the server system.

Abstract: A predictive failure model is used to generate a failure prediction associated with a node. A repair or backup action may also be determined to perform on the node based on the failure prediction.

Abstract: According to one embodiment, a malfunction predicting unit includes a level reduction unit, a first buffer gate unit, a second buffer gate unit, a comparator unit and a processing unit. The level reduction unit reduces an input digital signal to generate a level-reduced signal. The first buffer gate unit generates a first output signal. The first output signal has first or second level if the digital signal is or is not higher than a preset threshold level, respectively. The second buffer gate unit generates a second output signal. The second output signal has the first or second level if the level-reduced signal is or is not higher than the preset threshold level, respectively. The comparator unit compares the first and second output signals to generate a comparison result. The processing unit determines whether a malfunction will soon occur, based on the comparison result.

Abstract: Techniques for systematically gathering, organizing, and storing diagnostic data related to multiple monitored systems (e.g., multiple instances of a product or multiple products). A centralized repository is provided that is organized in a hierarchical manner to facilitate proper organization of the diagnostic data related to multiple monitored systems. In one embodiment, a root directory comprising one or more subdirectories is provided for storing diagnostic data collected for each monitored system. Multiple root directories may be provided under a common base directory for storing diagnostic data corresponding to multiple monitored systems. This enables correlation of diagnostic data across multiple monitored systems.

Abstract: In a particular embodiment, a method of monitoring interrupts during a power down event at a processor includes activating an interrupt monitor to detect interrupts. The method also includes isolating an interrupt controller of the processor from the interrupt monitor, where the interrupt controller shares a power domain with the processor. The method also includes detecting interrupts at the interrupt monitor during a power down time period associated with the power down event.

Abstract: Methods and systems are described that improve the alarming logic for Border Gateway Protocol (BGP) flapping events. Embodiments provide an alarm threshold on BGP flapping conditions and alert on BGP related events. A reduction in silent failures and network outage minutes is achieved.

Abstract: Technology is described for diagnosing problem causes in complex environments by using factorization of a plurality of features. An embodiment can include the operation of identifying a plurality of entities having entity weighting parameters. The entities may be computing devices. The plurality of features can be associated with a respective entity having feature weighting parameters, and an instance of the plurality of features can be associated with individual entity instances. A fault label can be applied for an ensemble entity. The plurality of features can be linked using the feature weighting parameter and the entity weighting parameter with a bilinear model. A further operation is estimating weighting values for the entity weighting parameters and the feature weighting parameters for use in a statistical model. The meaningful feature parameters can be found for the statistical model that are likely to be responsible for entity faults.

Abstract: Methods for automatically identifying and classifying a crisis state occurring in a system having a plurality of computer resources. Signals are received from a device that collects the signals from each computer resource in the system. For each epoch, an epoch fingerprint is generated. Upon detecting a performance crisis within the system, a crisis fingerprint is generated consisting of at least one epoch fingerprint. The technology is able to identify that a performance crisis has previously occurred within the datacenter if a generated crisis fingerprint favorably matches any of the model crisis fingerprints stored in a database. The technology may also predict that a crisis is about to occur.

Abstract: As set forth herein, a system identifies soft failures of devices. An interface captures transactional data between one or more users and one or more devices within the system. A data log receives the transactional data from the interface and stores the data as historical data for subsequent retrieval. A warning system evaluates the historical data in the data log to identify one or more devices that have a soft failure condition, wherein an alarm is output for each soft failure identified. A display module combines the historical data from the data log and one or more alarms from the warning system into a single display for review.

Abstract: Some embodiments of the present invention provide a system that controls a device that characterizes the health of a computer system power supply. During operation, a signature for the power supply is generated based on measurements of a set of performance parameters for the power supply. Then, the health of the power supply is characterized based on a comparison between the signature for the power supply and signatures for one or more other power supplies.

Abstract: Systems and methods of managing problem determination (PD) data provide for obtaining PD data from a plurality of data sources via an input/output (I/O) interface of a data management device and storing the PD data to a memory of the data management device. In addition, an automated diagnostic analysis of the PD data may be conducted on the data management device. An automated discovery manager may provide the ability to find new sources of PD data and to either reconfigure remote systems to send data to the data management device or to automatically retrieve data from remote systems on a configurable schedule. Dynamically updateable database of symptom information can also be used, wherein the data management device may include a dynamically updateable set of analysis modules with which to conduct analysis on the PD data.

Abstract: Systems and methods are provided for problem ticket resolution. A resolution component allocates a cause for each problem ticket, assigned by resolution teams to root cause clusters, to systems based on historical records that identify one of multiple historical systems as a cause for each historical problem ticket. If a corresponding number of causes allocated to a system is a predetermined amount greater than a corresponding historical number of causes allocated to the system, the resolution component may output a notification to a user interface to prompt a management action regarding the system, access a report associated with the system and output a notification to the user interface to prompt a management action regarding the system based on the report, or assign a set of problem tickets allocated to the system to a resolution team.

Abstract: The invention provides an information processing apparatus including: a plurality of abnormality detection sections provided in each of a plurality of detection target portions, that detect an abnormality caused by high temperature at a predetermined first frequency; an indication detecting section that detects an indication that the abnormality will occur; and a controller that controls to set the detection frequency of the plurality of abnormality detection sections to a second frequency which is higher than the first frequency, when the number of times that the indication is detected within a predetermined period is more than a predetermined number of times.

Abstract: A service is used to process files. The processing of the files is performed by worker services that are assigned to process a portion of the files. Each worker service that is processing a portion of the files is assigned a unique identifier. Using the identifier information, the set of worker services currently active are monitored along with the work assigned to each process. When a worker server determines that a worker service has failed, the work assigned to the failed worker service can be automatically determined and a new worker service can be started to process that work. Any new worker service that is started is assigned a unique identifier, so the work assigned to it can be similarly tracked.

Abstract: Systems and methods are disclosed for monitoring and managing data transactions, such as SQL transactions. In certain examples, a management subsystem generates an alert identifying degrading database transactions to facilitate preventative tuning or other maintenance. In particular, a monitor module tracks performance measurements (e.g., logical reads) of select transactions. A modeler correlates the performance measurements and assigns first performance model(s) to represent the performance measurements and predicted performance measurements of a particular transaction. A trend change module detects a significant change in a trend and/or variance of the performance measurements and can cause the modeler module to generate a second performance model to represent at least a portion of the performance measurements and the predicted performance measurements of the particular transaction.

Abstract: An abnormality detection apparatus includes: a performance information obtaining unit to obtain load information of a computer; a response time obtaining unit to obtain a response time of the computer; a first abnormality determination unit to determine whether the computer is in abnormal operation state based on the load information; a second abnormality determination unit to determine whether the computer is in abnormal operation state based on the response time, when the first abnormality determination unit determines that the computer is in abnormal operation state; and an abnormality notification unit to perform notification of an abnormality, when the second abnormality determination unit determines that the computer is in abnormal operation state.

Abstract: A service framework uses importance ranking information in making call decisions and/or wait-time decisions in connection with service requests. Each of the service requests has an importance ranking which reflects the importance of the information provided by the service to a task being performed. The health of a service may be controlled by permitting fewer (or more) service requests to be made to the service when the service is less (or more) healthy. The likelihood of a service request being made to the service may depend on the importance, ranking of the service request. When waiting for a response, a determination whether to continue waiting may be made based on the likelihood that the service has failed and based on the importance of the information to the task being performed.

Abstract: Provided is a method and system for calculating a bivariate Gaussian Q function using a univariate Gaussian Q function to thereby analyze an error probability of a communication system. A method of calculating an error probability of a communication system may include: receiving encoded communication information from another communication system; restoring information desired to be transmitted by another user by decoding the encoded communication system; and calculating the error probability by analyzing the restored information using a bivariate Gaussian Q function, the error probability indicating a probability that the restored information is different from the information desired to be transmitted by the other user. The calculating may include calculating the bivariate Gaussian Q function using a univariate Gaussian Q function.

Abstract: Testing of a computer program product by selecting a test node at which a snapshot is to be acquired to enable the completion of tests along test scenarios in the shortest time is provided. Information on a test scenario, information on a test node to which a test node makes a next transition, and other information are stored. For each test node, it is determined whether a branch path exists, and for each of these test nodes, an estimated execution time required to complete a test when a snapshot is acquired at a test node is calculated, an execution time required to complete a test without acquiring any snapshot is calculated, and a difference between the execution time and the estimated execution time is calculated as a reduced time. A test node with the longest reduced time is selected, and information for identifying the selected test node is output.

Abstract: The present invention relates to pattern recognition and classification, more particularly, to a system and method for meta-recognition which can to predict success/failure for a variety of different recognition and classification applications. In the present invention, we define a new approach based on statistical extreme value theory and show its theoretical basis for predicting success/failure based on recognition or similarity scores. By fitting the tails of similarity or distance scores to an extreme value distribution, we are able to build a predictor that significantly outperforms random chance. The proposed system is effective for a variety of different recognition applications, including, but not limited to, face recognition, fingerprint recognition, object categorization and recognition, and content-based image retrieval system.

Abstract: Predictive analysis systems and methods use and correlate data from historic events to identify trends and develop corrective maintenance and logistics actions in various technology areas, such as the transportation industry, the manufacturing industry, or any other suitable industry that experiences equipment failure. The predictive analysis method and also determines the adequacy and compliance of the requirements prior to the failure of a system in order to preemptively minimize and eliminate these negative outcomes. Current failure trends may be evaluated for one or several components of a given system, which may be the frequency of incidence of failure of one or more components of the system. Engineering instructions for repair may also be evaluated when a failure of one or more components of the system has taken place. On the basis of this information, future failure trends may be forecast and supply channels and maintenance and repair protocols may be updated in order to decrease component failure.

Abstract: A system, a computer program product and a method for failure prediction are implemented on an agent. The agent is installed on a machine to be monitored. The method includes detecting service data on the machine. A reference database is accessed, and a failure pattern is provided. The detected service data are analyzed in view of the provided failure pattern by applying a correlation mechanism, such that a prediction for future failures is generated and depicted as a result.

Abstract: Techniques for providing a method and system for multi-layer network analysis and design are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method, comprising determining, using a computer model of a network, a minimum probability of failure path between a pair of network nodes at a first network layer for one or more pairs of network nodes, calculating, using a processor and stored network data, a value for the minimum probability of failure for the identified minimum probability of failure path between the pair of network nodes at the first network layer for the one or more pairs of network nodes. The method may include identifying a maximum of the determined minimum probability of failure values for the one or more pairs of network nodes for the first network layer. The method may include probability of failure calculations for one or more secondary network layers.

Abstract: One embodiment of the present invention provides a system that systematically monitors and records performance parameters for a computer system. During operation, the system periodically measures values for a set of performance parameters associated with the computer system while the computer system continues operating. The system then records the values on a data storage device, wherein the recording process keeps track of temporal relationships between events in different performance parameters. The system subsequently allows the recorded values for the set of performance parameters to be analyzed.