Dynamic Network Selection Scoring System
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Solution Overview
Problem
Conventional methods for connecting users to communication networks do not consider factors such as application type, user status, or network conditions, leading to inefficient network resource allocation and user experience issues.
Innovation Solution
A system and method that identify network-related events for users, calculate a score based on various factors including user profiles, network availability, and application requirements, and dynamically select the most suitable network for the user, optimizing network resource allocation and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If network selection is based solely on network condition, then network resource allocation is simple, but user experience and application performance deteriorate
Solution Approach 1:
The patent changes the selection parameters from simple network condition metrics to a comprehensive scoring system that includes user profile parameters (data balance, talk balance, Roaming status), network parameters (signal strength, network type), and application parameters (application type, QoS requirements). This multi-dimensional parameter transformation resolves the contradiction by enabling better user experience without excessive complexity through structured parameter organization.
Solution Approach 2:
The system implements feedback mechanisms where the determined network selection is monitored for performance outcomes, and this feedback is used to refine future scoring decisions. The patent mentions using historical data and machine learning to improve network selection accuracy over time, creating a closed-loop system that continuously optimizes user experience while managing complexity.
2Reliability
If network selection considers multiple factors including user profile and application type, then user experience improves, but system complexity increases
Solution Approach 1:
The patent segments the network selection system into distinct functional modules: user profile analysis module, network condition assessment module, application requirement analysis module, and scoring calculation module. Each module handles specific factors independently, then integrates results through a standardized scoring framework. This segmentation reduces overall system complexity by creating manageable, independent components with clear interfaces.
Solution Approach 2:
The patent creates a universal scoring framework that can accommodate multiple factors (user profile, network conditions, application requirements) through a single standardized calculation mechanism. The scoring system serves multiple functions: evaluating different network options, incorporating diverse input factors, and providing a unified decision metric. This multi-functionality approach handles complexity through consolidation rather than proliferation of separate systems.
3Productivity
If dynamic network selection is implemented, then network resource allocation efficiency improves, but computational overhead increases
Solution Approach 1:
The patent implements partial dynamic evaluation by calculating scores for only the most relevant network options rather than all possible networks. The system identifies candidate networks based on basic filtering criteria first, then applies comprehensive scoring only to these reduced candidates. This partial action approach maintains allocation efficiency while reducing computational overhead by avoiding exhaustive evaluation of all networks.
Solution Approach 2:
The system performs preliminary network identification and filtering before executing the full scoring calculation. User profiles and application requirements are pre-analyzed to establish selection criteria in advance. Network options are pre-filtered based on basic compatibility requirements, so that when dynamic selection occurs, only refined scoring computation is needed rather than complete re-evaluation of all parameters.
Data Source
AI summary
A system, method, and computer program product are provided for determining a network for a user. In use, a network-related event associated with a user is identified. Additionally, a score is calculated for the user, in response to the identification of the event. Further, a network is determined for the user, based on the score.