Abstract: Systems, methods, and other embodiments for sorting-based assignment to optimize order fulfillment with short supply. One embodiment includes identifying a set of one or more distributions within a series of days. Sorting all demands of a first priority level occurring in the series of days by ascending order of size of the demand. For each demand of the first priority level in sorted order, (a) selecting an initial distribution during which the demand is scheduled to be fulfilled from the set of distributions, and (b) generating an indication that the demand can cannot be completely fulfilled, based on the size of the demand and the amount of supply available. Automatically arranging a graphical representation of a schedule of supplies and met and unmet demands for the series of days in a graphical user interface based at least on the indications generated for each demand.

Abstract: Systems, methods, and other embodiments associated with eviction of weakly correlated signals from collections are described. In one embodiment, a mock signal that has random signal properties is generated. A mock correlation coefficient between the mock signal and a measured time series signal from a collection of measured time series signals is then generated. A discrimination value that indicates a weak signal correlation is then selected, based at least in part on the mock correlation coefficient. A first measured signal is then identified from the collection of measured time series signals that has the weak signal correlation by determining that a first correlation coefficient between the first measured signal and a second measured signal is weak based on the discrimination value. The first measured signal is then evicted from the collection of signals in response to the determination that the first measured signal has the weak signal correlation.

Abstract: The disclosed embodiments relate to a system that automatically selects a prognostic-surveillance technique to analyze a set of time-series signals. During operation, the system receives the set of time-series signals obtained from sensors in a monitored system. Next, the system determines whether the set of time-series signals is univariate or multivariate. When the set of time-series signals is multivariate, the system determines if there exist cross-correlations among signals in the set of time-series signals. If so, the system performs subsequent prognostic-surveillance operations by analyzing the cross-correlations. Otherwise, if the set of time-series signals is univariate, the system performs subsequent prognostic-surveillance operations by analyzing serial correlations for the univariate time-series signal.

Abstract: The disclosed embodiments relate to a system that automatically selects a prognostic-surveillance technique to analyze a set of time-series signals. During operation, the system receives the set of time-series signals obtained from sensors in a monitored system. Next, the system determines whether the set of time-series signals is univariate or multivariate. When the set of time-series signals is multivariate, the system determines if there exist cross-correlations among signals in the set of time-series signals. If so, the system performs subsequent prognostic-surveillance operations by analyzing the cross-correlations. Otherwise, if the set of time-series signals is univariate, the system performs subsequent prognostic-surveillance operations by analyzing serial correlations for the univariate time-series signal.

Abstract: Systems, methods, and other embodiments for sorting-based assignment to optimize order fulfillment with short supply. One embodiment includes identifying a set of one or more distributions within a series of days. Sorting all demands of a first priority level occurring in the series of days by ascending order of size of the demand. For each demand of the first priority level in sorted order, (a) selecting an initial distribution during which the demand is scheduled to be fulfilled from the set of distributions, and (b) generating an indication that the demand can cannot be completely fulfilled, based on the size of the demand and the amount of supply available. Automatically arranging a graphical representation of a schedule of supplies and met and unmet demands for the series of days in a graphical user interface based at least on the indications generated for each demand.

Abstract: Systems, methods, and other embodiments are disclosed for data-driven user authentication misuse detection. In one embodiment, for a user authentication attempt to access a secure computer resource, user authentication log data having user attribute values is collected. The user authentication log data is transformed into a tracer data structure. The tracer data structure is augmented with timestamp data to generate an event data structure. It is determined whether the tracer data structure matches an existing tracer data structure stored in a rules database and, if not, a novelty flag is set to generate a new user behavior model filter. If the tracer data structure matches the existing tracer data structure: an existing user behavior model filter is applied, issuance of an alarm message or signal is controlled, and the existing user behavior model filter is updated based, at least in part, on the event data structure.

Abstract: Systems, methods, and other embodiments are disclosed for data-driven user authentication misuse detection. In one embodiment, for a user authentication attempt to access a secure computer resource, user authentication log data having user attribute values is collected. The user authentication log data is transformed into a tracer data structure. The tracer data structure is augmented with timestamp data to generate an event data structure. It is determined whether the tracer data structure matches an existing tracer data structure stored in a rules database and, if not, a novelty flag is set to generate a new user behavior model filter. If the tracer data structure matches the existing tracer data structure: an existing user behavior model filter is applied, issuance of an alarm message or signal is controlled, and the existing user behavior model filter is updated based, at least in part, on the event data structure.

Abstract: Systems, methods, and other embodiments are disclosed for data-driven user authentication misuse detection. In one embodiment, for each of multiple authentication attempts to a computing device by a user via user authentication log messages: user authentication log data having user attribute values is collected; the user authentication log data is transformed into a tracer data structure having the user attribute values organized in a common format; the tracer data structure is augmented with timestamp data to generate an event data structure, where the timestamp data represents a time at which the user authentication log data is observed by the computing device; a user behavior model filter, representing account usage patterns of the user, is updated based at least in part on the event data structure. A malicious authentication attempt to the computing device by a malicious user is detected based on, at least in part, the user behavior model filter.

Abstract: Systems, methods, and other embodiments are disclosed for data-driven user authentication misuse detection. In one embodiment, for each of multiple authentication attempts to a computing device by a user via user authentication log messages: user authentication log data having user attribute values is collected; the user authentication log data is transformed into a tracer data structure having the user attribute values organized in a common format; the tracer data structure is augmented with timestamp data to generate an event data structure, where the timestamp data represents a time at which the user authentication log data is observed by the computing device; a user behavior model filter, representing account usage patterns of the user, is updated based at least in part on the event data structure. A malicious authentication attempt to the computing device by a malicious user is detected based on, at least in part, the user behavior model filter.

Abstract: A macro-switch is described. This macro-switch includes facing integrated circuits, one of which implements optical waveguides that convey optical signals, and the other which implements control logic, electrical switches and memory buffers at each of multiple switch sites. Moreover, the macro-switch has a fully connected topology between the switch sites. Furthermore, the memory buffers at each switch site provide packet buffering and congestion relief without causing undue scheduling/routing complexity. Consequently, the macro-switch can be scaled to an arbitrarily large switching matrix (i.e., an arbitrary number of switch sites and/or switching stages).

Abstract: A macro-switch is described. This macro-switch includes facing integrated circuits, one of which implements optical waveguides that convey optical signals, and the other which implements control logic, electrical switches and memory buffers at each of multiple switch sites. Moreover, the macro-switch has a fully connected topology between the switch sites. Furthermore, the memory buffers at each switch site provide packet buffering and congestion relief without causing undue scheduling/routing complexity. Consequently, the macro-switch can be scaled to an arbitrarily large switching matrix (i.e., an arbitrary number of switch sites and/or switching stages).

Abstract: The disclosed embodiments provide a system that analyzes telemetry data from a computer system. During operation, the system obtains the telemetry data as a set of telemetric signals using a set of sensors in the computer system. Next, for each component or component location from a set of components in the computer system, the system applies an inferential model to the telemetry data to determine an operating environment of the component or component location, and uses the operating environment to assess a reliability of the component. Finally, the system manages use of the component in the computer system based on the assessed reliability.

Abstract: A system that provides fault tolerance in a parallel processing system. During operation, the system executes a parallel computing application in parallel across a subset of computing nodes within the parallel processing system. During this process, the system monitors telemetry signals within the parallel processing system. The system analyzes the monitored telemetry signals to determine if the probability that the parallel processing system will fail is increasing. If so, the system increases the frequency at which the parallel computing application is checkpointed, wherein a checkpoint includes the state of the parallel computing application at each computing node within the parallel processing system.