Abstract: In one example, a method includes receiving a feature vector that characterizes a call history for a telephone network subscriber, wherein the feature vector comprises respective categorical values for one or more categorical features and respective continuous values for one or more continuous features, and applying, to the categorical values, a first algorithm to determine a categorical score for the feature vector. The example method further includes applying, to the continuous values, an isolation forest algorithm to determine a continuous score for the feature vector, and outputting, in response to determining at least one of the categorical score for the feature vector and the continuous score for the feature vector indicate the feature vector is anomalous, an indication that the feature vector is anomalous.

Abstract: In general, techniques are described for parallelizing a high-volume data stream using a data structure that enables lockless access by a multi-threaded application. In some examples, a multi-core computing system includes an application that concurrently executes multiple threads on cores of the system. The multiple threads include one or more send threads each associated with a different lockless data structure that each includes both a circular buffer and a queue. One or more receive threads serially retrieve incoming data from a data stream or input buffer, copy data blocks to one of the circular buffers, and push metadata for the copied data blocks to the queue. Each of the various send threads, concurrent to the operation of the receive threads, dequeues the next metadata from its associated queue, reads respective blocks of data from its associated circular buffers based on metadata information, and offloads the block to a server.

Abstract: In general, this disclosure is directed to a software virtual machine that provides high-performance transactional data acceleration optimized for multi-core computing platforms. The virtual machine utilizes an underlying parallelization engine that seeks to maximize the efficiencies of multi-core computing platforms to provide a highly scalable, high performance (lowest latency), virtual machine. In some embodiments, the virtual machine may be viewed as an in-memory virtual machine with an ability in its operational state to self organize and self seek, in real time, available memory work boundaries to automatically optimize maximum available throughput for data processing acceleration and content delivery of massive amounts of data.