Abstract: Described herein is a device (e.g., IoT device) having bootstrap code that communicates with a secure global registry (e.g., private distributed shared blockchain database). The bootstrap code of the device uses a globally unique device identifier of the device to the secure global registry. The bootstrap code receives information from the secure global registry which the bootstrap code uses to obtain information to connect to a cloud-based endpoint. The bootstrap code can download an appropriate software development kit (SDK) associated with the particular cloud based, at least in part, upon the received information. The device can be registered in the secure global registry by creating a globally unique identifier for the device. An initial entry can be created in the secure global registry comprising the globally unique identifier, with the secure global registry stores current cloud-based endpoint information, if any, for the device.

Abstract: A sliding window buffer is implemented on a local computing device that places chunks of content from a data source into a local buffer for transmission on a per-chunk basis. A portion of memory in the local buffer can be re-used for a single data transmission operation until the content is fully transmitted to a remote computing device. Logical positions on the local buffer which correlate to inner positions on the data source are utilized to enable the sliding window buffer to retrieve and retransmit chunks of data, if necessary. An inner position indicates a byte location in the data source and a logical position indicates a corresponding byte position in the local buffer. The local computing device can utilize byte positions to retrieve and re-transmit chunks of data if, for example, the device fails to receive an acknowledgement from the remote computing device for any of the data.

Abstract: A sliding window buffer is implemented on a local computing device that places chunks of content from a data source into a local buffer for transmission on a per-chunk basis. A portion of memory in the local buffer can be re-used for a single data transmission operation until the content is fully transmitted to a remote computing device. Logical positions on the local buffer which correlate to inner positions on the data source are utilized to enable the sliding window buffer to retrieve and retransmit chunks of data, if necessary. An inner position indicates a byte location in the data source and a logical position indicates a corresponding byte position in the local buffer. The local computing device can utilize byte positions to retrieve and re-transmit chunks of data if, for example, the device fails to receive an acknowledgement from the remote computing device for any of the data.

Abstract: Described herein is a device (e.g., IoT device) having bootstrap code that communicates with a secure global registry (e.g., private distributed shared blockchain database). The bootstrap code of the device uses a globally unique device identifier of the device to the secure global registry. The bootstrap code receives information from the secure global registry which the bootstrap code uses to obtain information to connect to a cloud-based endpoint. The bootstrap code can download an appropriate software development kit (SDK) associated with the particular cloud based, at least in part, upon the received information. The device can be registered in the secure global registry by creating a globally unique identifier for the device. An initial entry can be created in the secure global registry comprising the globally unique identifier, with the secure global registry stores current cloud-based endpoint information, if any, for the device.

Abstract: A classification application identifies patterns and evidences within representative documents. The application constructs a classification rule according to an entity and an affinity determined from the patterns and evidences. The application processes the representative documents with the classification rule to evaluate whether the rules meet acceptance requirements. Subsequent to a successful evaluation, the application identifies confidence levels for patterns and evidences within other documents.

Abstract: A classification application identifies patterns and evidences within representative documents. The application constructs a classification rule according to an entity and an affinity determined from the patterns and evidences. The application processes the representative documents with the classification rule to evaluate whether the rules meet acceptance requirements. Subsequent to a successful evaluation, the application identifies confidence levels for patterns and evidences within other documents.

Abstract: A classification application identifies patterns and evidences within representative documents. The application constructs a classification rule according to an entity and an affinity determined from the patterns and evidences. The application processes the representative documents with the classification rule to evaluate whether the rules meet acceptance requirements. Subsequent to a successful evaluation, the application identifies confidence levels for patterns and evidences within other documents.

Abstract: A classification application identifies patterns and evidences within representative documents. The application constructs a classification rule according to an entity and an affinity determined from the patterns and evidences. The application processes the representative documents with the classification rule to evaluate whether the rules meet acceptance requirements. Subsequent to a successful evaluation, the application identifies confidence levels for patterns and evidences within other documents.