Abstract: An embodiment classifies, by analyzing data generated by a first edge device, the data into a sensitivity category in a set of sensitivity categories. An embodiment classifies, by analyzing the data, the data into a redundancy category in a set of redundancy categories. An embodiment classifies, into a region category in a set of region categories, a region in which the first edge device is located. An embodiment selects, by applying a set of allocation rules, a storage category of the data generated by the first edge device, the selecting resulting in a selected storage category, the set of allocation rules applied according to the sensitivity category, the redundancy category, and the region category. An embodiment causes storage of the data generated by the first edge device in a storage device in the selected storage category.

Abstract: A computer-implemented method, according to one approach, includes using a determined classification of a predetermined file to determine a data compliance ruleset that applies to data of the predetermined file. In response to a determination that the data of the predetermined file is scheduled to be moved and/or replicated from a source node to a target node of an edge computing environment, the determined data compliance ruleset is applied to the data of the predetermined file. The method further includes preventing the scheduled movement and/or replication of the data of the predetermined file from occurring, in response to a determination that the scheduled movement and/or replication of the data of the predetermined file violates at least one rule of the determined data compliance ruleset.

Abstract: Computer-implemented methods for management of data collection devices. Aspects include creating a cluster of data collection devices and a distributed meta-key manager for the cluster and providing an authentication key for each data collection device to access the distributed meta-key manager. Aspects also include collecting and storing data by one or more of the data collection devices and periodically perform a quorum check for each data collection device of the cluster. Aspects further include updating an operational mode of each data collection device based on the quorum check and offloading the stored data from a data collection device based on successful verification of the stored data and the operational mode of the data collection device.

Abstract: Embodiments of the invention are directed to wireless sport scoring. Aspects include detecting, by a sensor of a first user device, a scoring event between a first user and a second user and transmitting, by a wireless transmitter of the first user device, a signal indicating the scoring event to a scoring system. Aspects also include recording, in a memory of the first user device, a record of the scoring event and transmitting, by a wired transmitter of the first user device, the record of the scoring event to the scoring system based on detecting a wired connection between the first user device and the scoring system.

Abstract: Computer-implemented methods for management of data collection devices. Aspects include creating a cluster of data collection devices and a distributed meta-key manager for the cluster and providing an authentication key for each data collection device to access the distributed meta-key manager. Aspects also include collecting and storing data by one or more of the data collection devices and periodically perform a quorum check for each data collection device of the cluster. Aspects further include updating an operational mode of each data collection device based on the quorum check and offloading the stored data from a data collection device based on successful verification of the stored data and the operational mode of the data collection device.

Abstract: Provided is a computer-implemented method, system, and computer program product for detecting and processing a duplicate scene. A processor may receive image data from a plurality of images of a scene into a storage system, the image data including inference labels and contextual information associated with each of the plurality of images. The processor may detect, based on the inference labels and contextual information, that one or more images of the plurality of images is a duplicate of the scene. The processor may execute, in response to detecting that the one or more images of the plurality of images is the duplicate of the scene, an action related to the plurality of images.