Network Management via User Concentration Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current network management strategies, relying on local WiFi hotspots and cellular networks, often face overloading and cost issues due to unpredictable user demand, failing to dynamically adjust resources based on user concentration and roles.
Innovation Solution
A network management system that analyzes electronic scheduling information and other data to predict user demand, dynamically configuring network characteristics such as bandwidth and device deployment to optimize resource allocation based on user concentration and roles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static WiFi hotspots and cellular networks are used for network access, then network coverage is provided, but the networks become overloaded by user demand and incur high costs
Solution Approach 1:
The patent implements dynamic network management by continuously monitoring user concentration predictions and automatically adjusting network characteristics. The system transitions from static network configurations to dynamic ones where bandwidth allocation, device deployment, and network parameters are continuously optimized based on real-time user demand predictions, thereby preventing overload while maintaining coverage
Solution Approach 2:
The system performs preliminary actions by predicting user concentration before peak demand occurs. Using electronic scheduling information and historical data, the network manager anticipates future user concentrations and proactively configures network resources in advance, preventing network overload before it happens rather than reacting after the fact
2Productivity
If more network resources are allocated to handle user demand, then network capacity increases, but costs become prohibitive
Solution Approach 1:
The patent changes network parameters dynamically based on user concentration predictions. Instead of maintaining fixed high resource allocation, the system adjusts bandwidth, power levels, and device deployment parameters in real-time according to actual user demand, optimizing the balance between network capacity and operational costs
Solution Approach 2:
The network management system operates autonomously by automatically predicting user concentrations and configuring network resources without manual intervention. The system serves itself by making real-time decisions about resource allocation based on predicted demand, eliminating the need for continuous human monitoring and management while optimizing cost-efficiency
3Productivity
If network resources are dynamically adjusted based on user concentration, then network efficiency improves, but system complexity increases
Solution Approach 1:
The patent implements a universal network manager that performs multiple functions: predicting user concentrations, analyzing electronic scheduling information, making deployment decisions, and configuring network characteristics. This single multi-functional system handles all dynamic management tasks, reducing the need for multiple specialized systems while achieving high network efficiency
Data Source
AI summary
Various embodiments manage computing networks. In one embodiment, a set of network management data associated with one or more users is analyzed. The set of network management data includes at least electronic scheduling information associated with the one or more users. A concentration of users is predicted for a given location based on the analyzing. At least one network characteristic associated with the given location is performed based on at least the predicted concentration of users.