Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.

Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.

Abstract: Methods and arrangements for localizing an outage in a power grid. An outage is detected in a power grid, the power grid including interconnected nodes. At least one candidate network topology (in the power grid) with respect to the outage is determined, and power consumption information and measured voltages relative to the nodes in the power grid are received. Voltage at a plurality of the nodes in the power grid is estimated based on the received power consumption information and on the at least one candidate network topology, and a location of the outage is estimated, based on the estimated node voltages and measured voltages. Other variants and embodiments are broadly contemplated herein.

Abstract: A method of presenting data over a Web service interface includes: establishing, by a first computer process, a persistent transmission control protocol (TCP) network connection between the first computer process and a second computer process; dynamically allocating, by the second computer process, memory in response to receipt of static data over the persistent TCP network connection from the first computer process; updating, by the second computer process, the memory in response to receipt of dynamic data received over the persistent TCP network connection from the first computer process; and enabling, by the second computer process, a Web server to access the updated data for presentation by the Web service interface. The static data identifies a given entity and the dynamic data includes metric data provided for the entity.

Abstract: A system and method perform calibration of a forecast model for resource allocation. The method includes receiving inputs to the forecast model derived from historical data for a period of time, and executing the forecast model to obtain one or more forecast levels for each interval within the period of time, the forecast level corresponding with a quantified forecast of a forecast parameter that is forecast by the forecast model for the interval. Obtaining an actual level for each interval within the period of time according to the historical data is followed by comparing the one or more forecast levels with the actual level for the period of time according to a metric to adjust a mapping within the forecast model between values of the quantified forecast and the forecast levels based on the comparing to obtain a calibrated forecast model. The calibrated forecast model is used for resource allocation.

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: A method, system, and computer program product to perform infrastructure management include generating models of one or more work shifts, repair tasks, and safety tasks, each of the models including one or more variables, defining a constraint that affects at least one of the one of more variables of at least one of the models, and generating a scenario based on the models and the constraint. Solving for the one or more variables of each of the models of the scenario to determine resource pre-positioning and task scheduling, according to the scenario, is performed in order to perform the infrastructure management, the solving being based on achieving one or more objectives.

Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.

Abstract: A method, system, and computer program product to manage a network comprising a plurality of interconnected components are described. The method includes obtaining a set of all the components that are part of the network over time, and identifying one or more repeating patterns of components among the set of all the components as corresponding lower-level definitions to generate a hierarchical set of all the components. The method also includes obtaining time-varying information regarding topology and operational values within the network, and creating a representation of the network at a set of times based on the hierarchical set of all the components and the time-varying information.

Abstract: A method is disclosed comprising using a circuit recognition engine running on a computerized device to detect a number and type of devices in an integrated circuit. The method characterizes device variation by selecting a set of dominant active devices and performing simulation using the set of dominant active devices. Three different options may be used to optimize the number of simulations for any arc/slew/load combination. Aggressive reduction uses a minimal number of simulations at the cost of some accuracy loss, conservative reduction reduces the number of simulations with negligible accuracy loss, and dynamic reduction dynamically determines the minimum number of simulations needed for a given accuracy requirement.

Abstract: Methods and arrangements for localizing an outage in a power grid. An outage is detected in a power grid, the power grid comprising interconnected nodes. At least one candidate network topology (in the power grid) with respect to the outage is determined, and power consumption information and measured voltages relative to the nodes in the power grid are received. Voltage at a plurality of the nodes in the power grid is estimated based on the received power consumption information and on the at least one candidate network topology, and a location of the outage is estimated, based on the estimated node voltages and measured voltages. Other variants and embodiments are broadly contemplated herein.

Abstract: Systems and methods for determining a chip yield are disclosed. One system includes a first level integration solver and a second level integration solver. The first level integration solver is configured to obtain a first probability distribution function modeling variations within a chip and to perform a discontinuous first level integration with the first probability distribution function. In addition, the second level integration solver is implemented by a hardware processor and is configured to perform a continuous second level integration based on a second probability distribution function modeling variations between dies to determine the chip yield.

Abstract: A physical test integrated circuit has a plurality of repeating circuit portions corresponding to an integrated circuit design. A first of the portions is fabricated with a nominal block mask location, and additional ones of the portions are deliberately fabricated with predetermined progressive increased offset of the block mask location from the nominal block mask location. For each of the portions, the difference in threshold voltage between a first field effect transistor and a second field effect transistor is determined. The predetermined progressive increased offset of the block mask location is in a direction from the first field effect transistor to the second field effect transistor. The block mask overlay tolerance is determined at a value of the progressive increased offset corresponding to an inflection of the difference in threshold voltage from a zero difference. A method for on-chip monitoring, and corresponding circuits, are also disclosed.

Abstract: A physical test integrated circuit has a plurality of repeating circuit portions corresponding to an integrated circuit design. A first of the portions is fabricated with a nominal block mask location, and additional ones of the portions are deliberately fabricated with predetermined progressive increased offset of the block mask location from the nominal block mask location. For each of the portions, the difference in threshold voltage between a first field effect transistor and a second field effect transistor is determined. The predetermined progressive increased offset of the block mask location is in a direction from the first field effect transistor to the second field effect transistor. The block mask overlay tolerance is determined at a value of the progressive increased offset corresponding to an inflection of the difference in threshold voltage from a zero difference. A method for on-chip monitoring, and corresponding circuits, are also disclosed.

Abstract: Systems and methods for determining a chip yield are disclosed. One system includes a first level integration solver and a second level integration solver. The first level integration solver is configured to obtain a first probability distribution function modeling variations within a chip and to perform a discontinuous first level integration with the first probability distribution function. In addition, the second level integration solver is implemented by a hardware processor and is configured to perform a continuous second level integration based on a second probability distribution function modeling variations between dies to determine the chip yield.

Abstract: Systems and methods for determining a chip yield are disclosed. One method includes obtaining a first probability distribution function modeling variations within a chip and a second probability distribution function modeling variations between dies. Further, a discontinuous first level integration is performed with the first probability distribution function and a continuous second level integration is performed by a hardware processor based on the second probability function to determine the chip yield.

Abstract: A method of optimizing a plurality of objectives includes the steps of initializing a set of simplices; selecting a simplex from the set of simplices; computing one or more weights based at least in part on the selected simplex; and generating a point on a tradeoff surface by utilizing the one or more weights in a weighted-sum optimization.