Abstract: An input stream of events is processed to obtain an output stream of events. Consecutive events are selected from the input stream using a sliding window to obtain sliding window events, then a function is applied thereto to obtain an output result value. Operations of: outputting the output result value in the output stream; splitting the sliding window events into filter-complying events and pending events; applying the function on the pending events to obtain preliminary value(s); selecting, from the input stream, a second plurality of events; adding the second plurality of events to the sliding window events; removing, from the sliding window events, the filter-complying events to obtain a new set of sliding window events; and applying the function to the second plurality of events and the preliminary value(s) to obtain a new output result value, are then iteratively performed.

Abstract: A fault injection system for a software system, wherein the software system includes executable commands, events generated by commands and states representing a state of a state machine between two events, wherein a fault injection rule database is configured to provide a rule for injecting a selected fault, wherein the rule provides a fault injection decision in the occurrence of a selected command, a selected state during which fault injection is to occur and a condition under which fault injection is to occur; an estimator module is configured to determine when the selected state will occur related to the execution of the selected command and to provide a duration of a state as a time interval for fault injection, wherein the determination is based on a predictive time model; and an injector module is configured to execute the selected command and to inject the selected fault during the time interval.

Abstract: A database management system, comprising: a storage adapted for storing: a plurality of data objects organized according to a data model, and a plurality of stream operator wrappers each wrapping a stream operator and having at least one port for receiving, via a network, instructions for: scheduling activation of the wrapped stream operator, connecting the wrapped stream operator with another stream operator wrapped by another of the plurality of stream operator wrappers, and/or deploying the wrapped stream operator; a processing circuitry for executing the plurality of stream operator wrappers.

Abstract: A tracing system for managing failures of a service provided by a distributed system, the tracing system comprising a state machine store configured to store a distributed execution state machine (DESM), wherein states of the DESM correspond to predetermined milestones of the service and transitions of the DESM correspond to one or more instructions of the service; a logging unit configured to record events of the distributed system in a log store, wherein an event indicates a state and/or a transition of the DESM; a process reconstruction subsystem configured to reconstruct a trace of the DESM from the events stored in the log store; and a linking unit configured to link logging information of the distributed system to the states.

Abstract: A device detects anomalies on an input stream of events. Each event includes a value. The device has: a modeling unit configured to represent each event into at least one histogram over a predefined tree data structure to obtain a model of the input stream; a change detection and adaptation module configured to detect a long term change of the distribution of the events in the input stream based on the model of the input stream; and a scoring unit configured to calculate an anomaly score representing the probability of an anomaly in the input stream of events based on the model of the input stream and the detected long term change.

Abstract: A fault injection system for a software system, wherein the software system includes executable commands, events generated by commands and states representing a state of a state machine between two events, wherein a fault injection rule database is configured to provide a rule for injecting a selected fault, wherein the rule provides a fault injection decision in the occurrence of a selected command, a selected state during which fault injection is to occur and a condition under which fault injection is to occur; an estimator module is configured to determine when the selected state will occur related to the execution of the selected command and to provide a duration of a state as a time interval for fault injection, wherein the determination is based on a predictive time model; and an injector module is configured to execute the selected command and to inject the selected fault during the time interval.

Abstract: An input stream of events is processed to obtain an output stream of events. Consecutive events are selected from the input stream using a sliding window to obtain sliding window events, then a function is applied thereto to obtain an output result value. Operations of: outputting the output result value in the output stream; splitting the sliding window events into filter-complying events and pending events; applying the function on the pending events to obtain preliminary value(s); selecting, from the input stream, a second plurality of events; adding the second plurality of events to the sliding window events; removing, from the sliding window events, the filter-complying events to obtain a new set of sliding window events; and applying the function to the second plurality of events and the preliminary value(s) to obtain a new output result value, are then iteratively performed.

Abstract: A device for processing a stream of digital data, includes a memory configured to store executable instructions, and at least one processor coupled to the memory and configured to execute the instructions to manage a plurality of stream processing engines, each of the plurality of stream processing engines having a plurality of stream processing objects and simultaneously process the stream of digital data by the plurality of stream processing engines, and during the simultaneously processing the stream of digital data, to send an output of a first stream processing object of the plurality of stream processing objects of a first stream processing engine of the plurality of stream processing engines to an input of a second stream processing object of the plurality of stream processing objects of a second stream processing engine of the plurality of stream processing engines.

Abstract: A tracing system for managing failures of a service provided by a distributed system, the tracing system comprising a state machine store configured to store a distributed execution state machine (DESM), wherein states of the DESM correspond to predetermined milestones of the service and transitions of the DESM correspond to one or more instructions of the service; a logging unit configured to record events of the distributed system in a log store, wherein an event indicates a state and/or a transition of the DESM; a process reconstruction subsystem configured to reconstruct a trace of the DESM from the events stored in the log store; and a linking unit configured to link logging information of the distributed system to the states.

Abstract: A location-based caching system provides the ability for a mobile communication device to dynamically provide content related to a user's location. Content may comprise a series of map segments that anticipate the route traveled by a user of the mobile device. Other related content may also be provided, for example, point of interest information related to the route traveled. The system tracks a present location of the mobile device and predicts a future location of the mobile device. Based upon the prediction of future location, the caching module determines whether content related to the future location is presently stored on the mobile device. If appropriate content is not on the mobile device, the caching module retrieves the content from a content server via a network connection. The content information nay be contextually selected based upon, for example, user preferences, movement information, and device state information.