Abstract: A system includes a first processor configured to analyze packets received over a communication protocol system and determine one or more congestion indicators from the analysis of the data packets, the one or more congestion indicators being indicative of network congestion for data packets transmitted over a reliable transport protocol layer of the communication protocol system. The system also includes a rate update engine separate from the packet datapath and configured to operate a second processor to receive the determined one or more congestion indicators, determine one or more congestion control parameters for controlling transmission of data packets based on the received one or more congestion indicators, and output a congestion control result based on the determined one or more congestion control parameters.

Abstract: A control circuit accesses a memory having time series acquisition history data for members of a predetermined group. That control circuit is configured to predict at least one future aggregation of items on a per-member basis by (1) using machine learning to predict specific items in the at least one future aggregation of items, wherein the machine learning uses a training corpus comprising, at least in part, the aforementioned time series acquisition history data, and (2) using matrix factorization to predict a quantity of at least some of the specific items in the at least one future aggregation of items.

Abstract: Systems, apparatuses, and methods are provided herein for network incident management. A method for network incident management comprises aggregating network metrics associated with a monitored network in a historical network data database, identifying incidents based on the network metrics, generating a training data set based on the network metrics and the incidents, wherein the training data set comprises time series of network metrics as training input and incidents as labels, training an incident model using the training data set, receiving real-time network metrics from the network via the network interface, determining an incident prediction based on the incident model using the real-time network metrics as input, and causing a user interface device to provide an alert to a user based on the incident prediction.

Abstract: A system and process for providing a transaction infrastructure for matching user demand for a commodity such as energy across multiple sources and levels of distribution. A transaction hub is provided that normalizes transaction information across a plurality of distribution points. Scheduling and billing of users is managed at the hub, allowing fine and dynamic load balancing across multiple sources and levels.