Proximity Data Import Tool for Network Load Balancing
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Solution Overview
Problem
Current load balancing systems in large-scale networks face inefficiencies due to the lack of readily importable location data from external sources into proximity databases, leading to suboptimal response times as they rely heavily on probing processes for proximity information.
Innovation Solution
A proximity data import tool that imports location data from external sources, such as IP databases, and transforms it into proximity data for storage in proximity databases, using weighting logic to estimate device proximity to network zones based on geographic locations and round-trip times, thereby augmenting existing proximity data and reducing reliance on probing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system relies on probing processes to gather proximity information, then the proximity database can be populated with actual measured data, but the response time degrades due to the probing overhead
Solution Approach 1:
The system performs proximity measurements in advance by importing location data from external sources (IP databases, GPS data, cell tower information) and storing it in the proximity database before it is needed for load balancing decisions. This preliminary population of the database eliminates the need for time-consuming probing operations when making site selection decisions.
Solution Approach 2:
The patent introduces an intermediary import tool that acts as a bridge between external location data sources and the internal proximity database. This intermediary component transforms and imports location information from third-party sources, converting it into the appropriate format for the proximity database without requiring direct probing of the network.
2Device complexity
If the proximity database lacks comprehensive location data, then the system can maintain a simpler data import mechanism, but the site selection accuracy deteriorates
Solution Approach 1:
The import tool serves as an intermediary that handles the complexity of data transformation and validation, allowing the rest of the system to remain simple. It automatically transforms location data from various external formats into the standardized proximity database format, and validates the imported data against existing entries.
Solution Approach 2:
The system changes the parameters of proximity data by importing location information from external sources and transforming it into weighted proximity values. The import tool converts geographic coordinates, IP addresses, and other location parameters into standardized proximity metrics that can be directly used for load balancing decisions.
3Loss of information
If the system uses external location data sources, then the proximity information completeness improves, but the data transformation and validation complexity increases
Solution Approach 1:
The import tool acts as an intermediary layer between external location data sources and the proximity database, handling all transformation and validation complexity. It automatically converts various external data formats (IP databases, GPS coordinates, cell tower data) into the standardized proximity database format, and validates data quality without requiring manual intervention.
Solution Approach 2:
The import tool performs self-service by automatically transforming, validating, and importing data without requiring manual configuration or intervention. It autonomously handles data format conversion, validates imported entries against existing proximity data, and manages the integration process independently.
Data Source
AI summary
Systems, methods, and other embodiments associated with importing proximity data are provided. Device identification information and device location information associated with a device are received from a data source. An estimated proximity of the device to one or more network zones is determined based at least in part on the device location information. A device identifier and the estimated proximity of the device are stored in a proximity database that stores proximity data for devices relative to one or more network zones.