Wireless Network Optimization via Traffic Event Prediction
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Solution Overview
Problem
Wireless networks face inefficiencies due to unpredictable peak bandwidth demands from connected devices, leading to congestion and wasted resources, as they struggle to balance network loads during traffic events and incidents.
Innovation Solution
A computer-implemented method and system that predicts network usage by analyzing traffic events and historical data to generate a geographic polygon indicating impacted areas, allowing for preemptive balancing of network traffic and resource allocation across cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If peak bandwidth is defined by normal operation, then network equipment allocation is optimized for typical usage, but unexpected congestion incidents cause network dropping or ignoring requests
Solution Approach 1:
The system performs preliminary actions by detecting traffic events (accidents, congestion, weather conditions) and proactively balancing network load before peak bandwidth incidents occur. The network management system redirects traffic preemptively based on predicted network usage, preventing congestion before it impacts service reliability.
Solution Approach 2:
The system implements continuous feedback loops by monitoring traffic events, analyzing network usage patterns, and adjusting load balancing decisions in real-time. The network management system receives feedback from event detection systems and dynamically modifies resource allocation to maintain both efficiency and reliability.
2Reliability
If peak bandwidth is based on special or isolated incidents, then network reliability during incidents is improved, but capacity above average usage is wasted bandwidth that may go unused
Solution Approach 1:
The system dynamically adjusts network resource allocation based on real-time traffic event detection and predicted network usage. Rather than static over-provisioning, the network management system continuously adapts bandwidth allocation to actual needs, maintaining reliability during incidents while avoiding wasted capacity during normal operation.
Solution Approach 2:
The system changes network parameters (bandwidth allocation, resource distribution) based on detected traffic events and predicted usage patterns. The network management system modifies operational parameters dynamically, scaling resources up during predicted peak usage and scaling down during normal conditions to eliminate wasted bandwidth.
3Reliability
If network equipment is deployed to handle peak bandwidth from incidents, then network reliability is improved, but network equipment costs and complexity increase
Solution Approach 1:
The network management system performs self-service by automatically detecting traffic events, predicting network usage, and balancing load without requiring manual intervention or additional complex infrastructure. The system uses existing network monitoring capabilities combined with event detection to autonomously manage bandwidth allocation.
Solution Approach 2:
The system replaces mechanical/physical network expansion (adding more equipment) with intelligent software-based load balancing and traffic redirection. Rather than deploying additional hardware to handle peak loads, the network management system uses algorithms to dynamically allocate existing resources, reducing equipment complexity and costs.
4Loss of energy
If network equipment is reduced to match normal operation bandwidth, then network equipment costs decrease, but the network cannot handle unexpected congestion incidents
Solution Approach 1:
The network management system takes preliminary action by detecting traffic events and proactively balancing load before congestion incidents occur. This allows the network to maintain smaller, more cost-effective equipment while still handling incidents through preemptive traffic redistribution rather than relying on excess capacity.
Solution Approach 2:
The system achieves adaptability through dynamic parameter changes in bandwidth allocation and resource distribution based on detected traffic events. The network management system modifies operational parameters in real-time, enabling cost-effective infrastructure to adapt to varying demand conditions without requiring peak-capacity equipment.
Data Source
Figure 1A~1B
Figure 2
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AI summary
Methods and apparatuses are provided for optimizing a wireless network. A description of a traffic incident is received. An impact area is generated from the description. A geographic polygon is generated based on the impact area. The network usage of the geographic polygon is determined. A message including the network usage for the geographic polygon may be transmitted to a mobile network operator.