Distributed Querying Computing Hubs Data Retrieval
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Solution Overview
Problem
Obtaining device-generated data from computing hubs is challenging due to their distributed nature, requiring direct access to individual hubs and often restricted by data policies that allow only summarized or aggregated data to be sent to service provider environments, limiting its availability for uses like deep learning and troubleshooting.
Innovation Solution
A distributed query system is implemented, where a program code function is executed on multiple computing hubs to retrieve device-generated data, allowing unprocessed data to be sent to a service provider environment, enabling efficient aggregation and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If direct access to individual computing hubs is used to obtain device-generated data, then data retrieval is possible, but system complexity and difficulty of operation increase due to the distributed nature of hubs
Solution Approach 1:
The patent introduces a service provider environment as an intermediary between end users and distributed computing hubs. This intermediary manages the complexity of data retrieval by handling queries, authentication, and coordination across multiple hubs, allowing users to access device-generated data without directly interacting with individual hubs.
2Reliability
If data policies restrict data transmission to only summarized or aggregated data, then security and control are improved, but data usability for deep learning and troubleshooting deteriorates
Solution Approach 1:
The patent segments data access into different levels: aggregated data for general purposes and unprocessed device-generated data for specialized applications like deep learning and troubleshooting. This segmentation allows the system to comply with data policies for general access while enabling advanced analytics when appropriate authorization and infrastructure are provided.
3Productivity
If unprocessed device-generated data is transmitted to service provider environment, then data analysis capability is improved, but data transmission complexity and resource requirements increase
Solution Approach 1:
The patent implements preliminary actions by establishing data lakes and processing pipelines in advance within the service provider environment. These pre-configured infrastructure elements are ready to receive and process unprocessed device-generated data, reducing the complexity of ad-hoc data transmission and enabling rapid analysis when needed.
Data Source
AI summary
A technology is described for distributed querying of computing hubs for device-generated data. In one example, computing hubs may provide a storage service to devices included in a local device network, and the devices may send device-generated data to the computing hubs to be stored by the storage service. A distributed query may be initiated by identifying the computing hubs that have the device-generated data stored on the computing hubs and sending a message containing query instructions to the computing hubs. The query instructions, when executed on the computing hubs, retrieve the device-generated data from the storage service included on the computing hubs, and the computing hubs may send the device-generated data to a service provider environment.