Multi-Link Load Balancing Using Idle Capacity Metrics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing load balancing techniques in vehicle-to-base station communication networks fail to account for the variability in communication link performance, leading to unpredictable network congestion due to sudden surges in demand.
Innovation Solution
Implement opportunistic load balancing by measuring both performance and idle capacity metrics for multiple communication links, using signal-to-noise ratio, carrier-to-noise ratio, and other characteristics to dynamically select base stations that can handle new network sockets without causing congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If load balancing is performed based on previously-determined superior communication links, then connection quality is improved, but the links may have degraded by the time traffic is routed
Solution Approach 1:
The system performs preliminary actions by continuously measuring radio channel performance metrics and idle capacity metrics before traffic routing occurs. This allows the load balancer to have up-to-date information about link conditions ready in advance, enabling faster and more accurate routing decisions when traffic needs to be directed.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring radio channel performance metrics and idle capacity metrics, then using this information to adjust load balancing decisions. This closed-loop approach ensures that routing decisions are based on current link conditions rather than outdated information.
2Reliability
If traffic is routed over communication links with superior performance, then quality of connections is improved, but network congestion occurs when demand suddenly increases
Solution Approach 1:
The system measures idle capacity metrics in advance to determine how much additional traffic each link can handle before becoming congested. This preliminary assessment allows the load balancer to route traffic proactively to links with sufficient capacity, preventing congestion before it occurs.
Solution Approach 2:
The system dynamically adjusts load balancing decisions based on real-time changes in network conditions. When demand suddenly increases, the load balancer can quickly redirect traffic to links with available capacity, adapting to changing conditions to maintain both quality and capacity.
3Measurement precision
If multiple communication links are monitored for load balancing, then routing accuracy is improved, but measurement and processing complexity increases
Solution Approach 1:
The system segments the measurement process by dividing the network into individual links, each with its own performance metrics and idle capacity measurements. This segmentation allows for targeted, manageable monitoring of each link's conditions rather than attempting to measure the entire network as one complex unit.
Solution Approach 2:
The transceivers perform self-measurement of radio channel performance metrics and idle capacity metrics without requiring external intervention. This self-service capability reduces the complexity of centralized measurement systems while maintaining accurate routing information.
Data Source
AI summary
Systems and methods are provided for opportunistic load balancing across one or more communication links supported by one or more base stations. As part of the opportunistic load balancing process, a load balancer may measure a performance metric and an idle capacity metric for the one or more communication links. In some embodiments, the load balancer may directionally measure the performance metric and the idle capacity metric. Based on the measured metrics, the load balancer may determine a candidate base station for a network socket. The load balancer may then establish the network socket with the candidate base station. As a result, the load balancer may help alleviate network congestion.