Network Block Geo-locator Using Intermediate Assignment Generators
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for determining the geographic location of network entities face challenges due to varying levels of accuracy and trustworthiness in information sources, which are dynamic and require adaptable methods to ensure reliable location determination.
Innovation Solution
A system and method that utilize a network block geo-locator to gather and process geo-location data from multiple sources, employing intermediate assignment generators and classifiers to create and validate geographic location assignments, allowing for adaptable and accurate determination of network block locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple information sources are used to determine geographic location, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system segments the geographic location determination process into distinct functional modules: data collection module, data processing module, and location determination module. Each module handles specific tasks independently, managing complexity while improving precision through specialized processing of geographic data from multiple sources.
Solution Approach 2:
The patent introduces intermediate data structures and processing layers that mediate between raw data from multiple information sources and the final location determination. These intermediaries organize and validate data before processing, enabling accurate location determination while managing system complexity through structured data flow.
2Adaptability or versatility
If the system is hard-wired to specific data sources, then device complexity is reduced, but adaptability deteriorates
Solution Approach 1:
The system implements a universal data collection module that can interface with multiple types of information sources (GPS devices, network entities, mobile devices) through standardized protocols. This multi-functional approach enables the system to adapt to different data sources without increasing fundamental system complexity, as the same modular structure handles various input types.
Solution Approach 2:
The patent creates a dynamic system where the set of active information sources can be modified at runtime based on availability and reliability. The system can dynamically add or remove data sources without reconfiguration, achieving high adaptability while maintaining manageable complexity through flexible, runtime-adjustable architecture.
3Adaptability or versatility
If data sources are highly dynamic, then adaptability is improved, but reliability deteriorates
Solution Approach 1:
The system implements feedback mechanisms that continuously monitor the reliability and quality of data from dynamic information sources. Based on this feedback, the system adjusts its processing to weight or exclude unreliable sources, maintaining location determination reliability even as data sources change dynamically. The feedback loop enables real-time quality assessment and adaptive response to varying source reliability.
Data Source
AI summary
Described herein are a method and a system to assign geographic locations to network blocks. A particular embodiment of the system includes a set of intermediate assignment generators, each intermediate assignment generator being associated with at least one of a plurality of network data sources, each intermediate assignment generator being configured to generate an intermediate assignment for at least one of the plurality of network data sources, a set of classifiers each coupled to at least one of the intermediate assignment generators, each classifier being associated with at least one of the plurality of network data sources, each classifier being configured to generate at least one classification based on at least one of the intermediate assignments and corresponding training data, and an intermediate assignment selector to select a best intermediate assignment based on the classifications generated by the set of classifiers, the best intermediate assignment corresponding to a geographic location of a network block.