LTE Application-Level Load Balancing for Network Congestion
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Solution Overview
Problem
Current LTE radio access networks face congestion issues during peak traffic times, major events, and natural disasters, as they rely on Layer 2 resource blocks for traffic distribution, leading to inefficient traffic management.
Innovation Solution
Implementing intelligent network load balancing by analyzing application-level load balancing factors to dynamically distribute data packets across network devices, prioritizing traffic based on factors like application requirements, user profiles, and device capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If Layer 2 resource blocks are used for traffic distribution, then traffic can be delivered via the radio network, but the network becomes congested during peak traffic times and major events
Solution Approach 1:
The patent changes the load balancing parameter from Layer 2 resource blocks to application-level metrics including backhaul link utilization, application performance requirements, and network congestion indicators. This enables dynamic adjustment of traffic distribution based on real-time network conditions rather than static Layer 2 allocations, resolving the contradiction between maintaining traffic delivery and preventing congestion.
Solution Approach 2:
The invention implements dynamic load balancing that continuously monitors network conditions and adjusts traffic distribution in real-time. The system dynamically shifts traffic between eNodeBs based on changing congestion levels, backhaul capacity, and application requirements, transforming the static Layer 2 resource block allocation into a flexible, adaptive system that maintains reliability during peak traffic times.
2Device complexity
If traditional load balancing is used, then traffic distribution is simple, but it cannot prioritize high-priority traffic during congestion
Solution Approach 1:
The patent applies local quality by treating different applications and traffic flows with different prioritization levels. Instead of uniform load balancing, the system identifies high-priority applications (e.g., emergency services, real-time communication) and directs them to eNodeBs with available capacity, while lower-priority traffic is routed to less congested paths. This differentiated approach enables traffic prioritization without requiring complete system redesign.
Solution Approach 2:
The invention implements feedback mechanisms that monitor application performance, network congestion levels, and backhaul link utilization. This feedback information is used to continuously adjust load balancing decisions, enabling the system to adapt to changing conditions and prioritize traffic dynamically. The feedback loop transforms simple static load balancing into an intelligent, responsive system.
3Ease of operation
If Layer 2 traffic distribution is used, then adjacent eNodeBs can exchange traffic status information, but traffic distribution suddenly becomes congested during elevated traffic times
Solution Approach 1:
The patent transitions from two-dimensional Layer 2 resource block management to multi-dimensional application-level load balancing that incorporates backhaul link utilization, application performance requirements, user equipment capabilities, and network congestion indicators. This additional dimensional information enables more efficient traffic distribution decisions that prevent congestion during elevated traffic times while maintaining the underlying X2 interface for status information exchange.
Data Source
AI summary
A network device may receive an application level load balancing factor, and instruct another network device to load balance data packets based on an analysis of the application level load balancing factor.