Abstract: The present disclosure relates to synchronizing entity identifiers across multiple data centers. In some embodiments, an entity identifier translation server may be deployed within a cloud-based distributed environment. The entity identifier translation server may receive data from multiple different data centers and detect changes/updates to entity identifiers within the data centers. In response to detected changes, the entity identifier translation server may identify one or more corresponding entity identifiers within the other data centers. For each of the corresponding entity identifiers within the other data centers, the entity identifier translation server may determine whether or not the corresponding entity identifier is to be synchronized with the newly-changed entity identifier in the first data center, and if so, may initiate synchronization processes.

Abstract: The present disclosure generally relates to storing, processing, and classification of content resources, such as documents, web-based resources, and other content. More particularly, the present disclosure describes techniques for distributed storage of network session data in hierarchical data structures stored on multiple servers and/or physical storage devices, and techniques for analyzing and classifying the distributed hierarchical structures. Such techniques may include executing different machine-learning algorithms on different servers and/or different storage devices, and generating node mapping data between a plurality of different hierarchical structures and a top-level derivative hierarchy that references the underlying hierarchical structures in order to access and manage the different distributed taxonomies within the underlying hierarchical structures.

Abstract: The present disclosure relates to synchronizing entity identifiers across multiple data centers. In some embodiments, an entity identifier translation server may be deployed within a cloud-based distributed environment. The entity identifier translation server may receive data from multiple different data centers and detect changes/updates to entity identifiers within the data centers. In response to detected changes, the entity identifier translation server may identify one or more corresponding entity identifiers within the other data centers. For each of the corresponding entity identifiers within the other data centers, the entity identifier translation server may determine whether or not the corresponding entity identifier is to be synchronized with the newly-changed entity identifier in the first data center, and if so, may initiate synchronization processes.

Abstract: The present disclosure generally relates to storing, processing, and classification of content resources, such as documents, web-based resources, and other content. More particularly, the present disclosure describes techniques for distributed storage of network session data in hierarchical data structures stored on multiple servers and/or physical storage devices, and techniques for analyzing and classifying the distributed hierarchical structures. Such techniques may include executing different machine-learning algorithms on different servers and/or different storage devices, and generating node mapping data between a plurality of different hierarchical structures and a top-level derivative hierarchy that references the underlying hierarchical structures in order to access and manage the different distributed taxonomies within the underlying hierarchical structures.

Abstract: An integrated circuit cast on a single die having a plurality of receivers in a receiver region, a plurality of transmitters in a transmitter region, and a spatial separation region having a plurality of n-type and p-type subregions disposed on the single die to separate the transmitter region from the receiver region. The pn-junctions between the n-type and p-type subregions are reverse-biased thereby reducing or eliminating coupling of noise and crosstalk between the transmitter and receiver is reduced.