Geohash Auto-Segmentation for Wireless Network Clustering
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Solution Overview
Problem
Current methods for geo-segmenting terrestrial regions, such as those used in wireless communication networks, lack an easy and adaptive solution to divide areas into smaller sections based on communication-derived criteria, leading to inefficiencies in managing increased wireless communication traffic and requiring significant effort for re-segmentation.
Innovation Solution
A method that utilizes Geohash coordinates to select nodes, subdivide areas, and sequence through subareas to identify and cluster regions based on threshold parameters, allowing for auto-adaptable segmentation by increasing the Geohash string length, thereby generating clusters that do not exceed predetermined thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed segmentation methods (telephone country codes, area codes, postal zip codes) are used to divide terrestrial regions, then the segmentation is simple and established, but considerable effort is required to re-segment the region when density increases
Solution Approach 1:
The patent implements dynamic segmentation by allowing the Geohash string length to vary based on traffic density. The system automatically adjusts the number of hash characters (e.g., 6, 7, 8, 9, 10) to match the required granularity level, enabling the segmentation to adapt dynamically to changing density conditions without manual re-segmentation efforts
Solution Approach 2:
The patent changes the parameter of Geohash string length to control segmentation granularity. By varying the string length parameter, the system can produce different levels of detail in segmentation matching the current traffic density, transforming a static segmentation system into one that adapts to changing conditions
2Adaptability or versatility
If Geohash is used to segment terrestrial regions, then the segmentation can be hierarchical and scalable, but current solutions do not provide an easy method to automatically and/or adaptively segment a terrestrial area into smaller sections
Solution Approach 1:
The system performs self-service by automatically detecting traffic density thresholds and initiating segmentation operations without human intervention. When traffic density exceeds predefined thresholds, the system autonomously divides regions into smaller Geohash cells and assigns them to appropriate network nodes, eliminating the need for manual analysis and re-segmentation
Solution Approach 2:
The patent implements feedback mechanisms where traffic density measurements are continuously monitored and fed back into the segmentation system. When density thresholds are exceeded, the feedback triggers automatic segmentation adjustments, creating a closed-loop system that self-corrects based on real-time conditions
3Reliability
If systematic analysis is performed to determine how and where to deploy additional towers when traffic increases, then network optimization can be achieved, but considerable effort and time are required
Solution Approach 1:
The patent applies preliminary action by pre-defining traffic density thresholds and segmentation rules before network optimization is needed. When traffic increases, the system already has the framework in place to automatically execute segmentation and node assignment, eliminating the need for time-consuming systematic analysis and enabling rapid response to traffic changes
Data Source
AI summary
A method, apparatus and network node for clustering a terrestrial area based on Geohash coordinates by selecting a node based on a Geohash area identified by a Geohash string of a predetermined length; subdividing the Geohash area into subareas by increasing the Geohash string by a length of one; and sequencing through the subareas to identify subarea/subareas that exceed a threshold number of a selected parameter. For subareas not exceeding the threshold number of the selected parameter, combining those subareas into clusters without exceeding the threshold number of the selected parameter in respective clusters. For subareas exceeding the threshold number of the selected parameters, subdividing those subareas into further subareas by increasing the Geohash string by one and sequencing through the further subareas to place the further subareas into clusters without exceeding the threshold number of the selected parameter.