Navigation Stack Management for Cross-Account Data Updates
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Solution Overview
Problem
Existing data systems face challenges in accurately determining and updating quantitative or categorical values across isolated data structures, leading to performance limitations and user frustration, especially when dealing with cross-account adjustments and industrial process controls where metrics from one stage affect downstream processes.
Innovation Solution
The system generates and updates navigation stacks on client computing devices by obtaining messages from clients, determining values associated with different navigation screens, and inserting them into a sequence to display appropriate screens, while also encrypting data for security and efficiently storing transaction data using symmetric block cipher encryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the system updates navigation stacks and displays multiple navigation screens, then user interface performance and user experience are improved, but device complexity and processing load increase
Solution Approach 1:
The navigation system is segmented into a navigation stack data structure that separates navigation state from display rendering. The stack maintains a sequence of navigation screens with their associated values, allowing independent management of navigation logic and visual presentation. This segmentation enables efficient updates without increasing overall system complexity.
Solution Approach 2:
The navigation stack is designed as a dynamic data structure that automatically manages the sequence of navigation screens. When values change, the system dynamically inserts or removes screen entries from the stack, maintaining optimal navigation flow. This dynamic behavior abstracts away the complexity of manual navigation state management from the user interface layer.
2Reliability
If the system encrypts data using symmetric block cipher encryption, then data security is improved, but processing time and computational resources increase
Solution Approach 1:
The patent uses symmetric block cipher encryption which creates a copy of the data in an encrypted form. The encryption process generates an encrypted version of navigation and transaction data that can be stored and transmitted securely. The symmetric nature allows efficient encryption and decryption with comparable computational cost, reducing the processing burden compared to asymmetric encryption.
3Measurement precision
If the system determines values based on messages from client devices, then data accuracy and cross-account updates are improved, but network communication overhead and processing time increase
Solution Approach 1:
The system performs preliminary validation of message formats and value ranges before processing navigation stack updates. By checking message integrity and value consistency in advance, the system avoids time-consuming error handling during critical navigation operations. This preliminary action ensures data accuracy while minimizing processing delays.
Solution Approach 2:
The navigation stack system implements feedback mechanisms where updated values are validated against existing navigation state and business rules. The system provides feedback about value consistency and navigation validity, allowing for rapid correction of errors without requiring complete reprocessing of navigation sequences. This feedback loop maintains data accuracy while reducing overall processing time.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances user interface performance, efficiently stores and encrypts data, and reduces processing load, allowing for seamless cross-account updates and improved data management in complex systems.
Implementation Method 1
efficiently storing transaction data using symmetric block cipher encryption
Data Source
AI summary
A method includes obtaining a first message from a client computing device, the first message including a first value indicating a change in a resource utilization. The method also includes obtaining a sequence of previous values associated with previous resource utilizations. The method also includes determining a predicted schedule of values for a field of a record indicating resource use using a neural network based on the first value and the sequence of previous values. The method also includes determining whether a set of alert criteria is satisfied based on the predicted schedule of values. The method also includes sending a second message to the client computing device in response to a determination that the set of alert criteria is satisfied.