International Business Machines Corporation

Daniel De Souza Casali

Abhishek Jain

Sarbajit Kumar Rakshit

Sarvesh S Patel

Adriana Pellegrini Furnielis

Nicolas Jean-Baptiste Joly

Joseph W Dain

Frank N Lee

Asmahan Ali

Christopher J Vollmar

Eduardo Ferreira Tomaz

A computer resource disparity is detected. The computer resource disparity is related to performing a computing task. The computer resource disparity is located proximate to a first location. A set of one or more autonomous vehicles capable of being adjacent to the first location is identified. An autonomous vehicle computing inquiry is generated. The inquiry is generated based on the first location and based on the computer resource disparity. The autonomous vehicle computing inquiry is transmitted based on the first location. An autonomous vehicle status is received in response to the autonomous vehicle computing inquiry that includes a set of one or more computing resources of the set of autonomous vehicles. A first autonomous vehicle of the set of autonomous vehicles is assigned to perform the computing task. The assignment is based on the set of computing resources of the set of autonomous vehicles.

Edge computing autonomous vehicle infrastructure

A method, system, and computer program product for context relevant data migration to a cloud server with job rescheduling are provided. The method identifies a contextual situation associated with at least a portion of data sets available for migration to a cloud server by a set of data sources. The method identifies an application associated with the contextual situation. A set of use characteristics are determined for the data sets based on the contextual situation and the application. Bandwidths are determined for one or more data sources. One or more data sets are selected for prioritization based on a contextual relevance, the set of use characteristics, and the bandwidths for the one or more data sources. The method schedules a job processing sequence of the selected one or more data sets based, at least in part, on the contextual relevancy, the set of use characteristics, and the bandwidths.

Context relevant data migration and job rescheduling

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.

Zero trust management for data collection devices

In an approach to improve mobile computation while traveling by dynamically generating one or more routes base on computing resource requirements of one or more endpoint devices. Embodiments identify, in real time, a plurality of autonomous vehicles, wherein the plurality of autonomous vehicles are traveling along a common route. Further embodiments, adjust, in real time, relative positions and speeds of the plurality of autonomous vehicles to maintain the plurality of autonomous vehicles within a predetermined geographic area while traveling along the common route, and wherein the predetermined geographic area is sufficient to collectively provide an amount of edge computing resources to satisfy one or more computing resource requirements of the one or more endpoint devices located within a first autonomous vehicle. Additionally, embodiments adjust, in real time, a route of the first autonomous vehicle based on the common route of the plurality of autonomous vehicles providing the edge computing resources.

Dynamic route recommendation based on mobile computation

In an approach for ensuring data protection and control in a distributed hybrid multi-cloud environment with Kubernetes clusters, a processor determines whether a respective quorum of the set of clusters are online. A processor, responsive to determining that a respective quorum of the set of clusters are online, determines whether one or more applications of the cluster are running on another cluster of the set of clusters. A processor, responsive to determining the one or more applications of the cluster are not running on another cluster of the set of clusters, determines whether the cluster is designated as a highest priority cluster. A processor, responsive to determining the cluster is designated as the highest priority cluster, determines whether a main cluster of the set of clusters is online. A processor, responsive to determining the main cluster is online, scales a new custom resource to one (1).

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Elmhurst, NY, United States of America

Daniel De Souza Casali