Distributed Data Storage With Synchronized Updates for Real-Time Analytics
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Solution Overview
Problem
Existing security procedures for IoT devices are inadequate, leading to compromised enterprise data stores, and distributed state updates in multiple servers are error-prone and impossible without a lock, while current databases sacrifice read operations for fast writes, limiting real-time data analysis and requiring expensive manual configuration.
Innovation Solution
A method for secure device authentication and role-based access control, combined with time-synchronized distributed state updates and optimized database configurations that allow simultaneous state updates across servers, enabling real-time data processing and reducing manual configuration costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional authentication and access control procedures are used, then device access is granted based on credentials, but security is compromised when credentials are stolen or compromised
Solution Approach 1:
The system performs preliminary actions by establishing a trusted perimeter before data exchange occurs. Devices must be authenticated and authorized before they can access enterprise data stores, preventing compromised credentials from being used to extract or delete data.
Solution Approach 2:
The patent introduces an intermediary trusted perimeter mechanism that mediates between external devices and enterprise data stores. This intermediary layer validates and controls all data transfer operations, preventing direct access even if credentials are compromised.
2Device complexity
If distributed state update techniques are implemented without locks, then system complexity is reduced, but update accuracy and consistency deteriorate
Solution Approach 1:
The system segments the distributed state update process into distinct phases: update initiation, propagation to multiple servers, and confirmation collection. This segmentation allows coordinated updates across geographically separated servers without requiring traditional locking mechanisms.
Solution Approach 2:
The patent implements feedback mechanisms where servers confirm successful state updates to a coordinator. This feedback loop ensures that state changes are propagated consistently across all servers without requiring locks, maintaining update accuracy while reducing system complexity.
3Productivity
If databases are configured for fast writes, then data ingestion speed is improved, but read operation performance deteriorates
Solution Approach 1:
The system segments read and write operations into separate processing paths. Write operations are handled by ingestion services that optimize for speed, while read operations are served by query services that optimize for analytical performance, allowing both to operate at optimal speeds simultaneously.
Solution Approach 2:
The patent introduces an intermediary layer (data lakes and query services) between the database and analytical operations. This intermediary allows fast writes to continue while providing optimized read paths for real-time data analysis, eliminating the trade-off between write speed and read performance.
4Productivity
If real-time data analysis is enabled, then analytical capability is improved, but system complexity and configuration costs increase
Solution Approach 1:
The system implements self-service capabilities where the data platform automatically provides real-time analytical capabilities without requiring manual configuration. Users can perform real-time data analysis on ingested data through standardized interfaces, eliminating the need for expensive manual configuration and reducing system complexity.
Data Source
AI summary
In some implementations, a computer-implemented method includes receiving a state update command. The method further includes, in response to the state update command, sending a command to perform a state update in a first server of a plurality of servers and queueing incoming requests for access to the plurality of servers. The method further includes receiving confirmation from the first server that the state update was successful. The method further includes, after receiving the confirmation, sending a respective command to the plurality of servers to perform the state update and a scheduled update time associated with the state update. The method further includes receiving a respective state update message from a subset of the plurality of servers that the state update was successful and after receiving the state update message, transmitting the queued incoming requests to the subset of the plurality of servers.


