Multi-Link Load Balancing for Congestion-Aware Base Station Selection
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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 increases in network demand.
Innovation Solution
Implement opportunistic load balancing by measuring both performance and idle capacity metrics for multiple communication links, and dynamically selecting base stations that can handle new network sockets without causing congestion, using signal-to-noise ratio, carrier-to-noise ratio, and bandwidth estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If load balancing is performed based on current communication link performance, then traffic routing is optimized, but the performance may have degraded by the time traffic is routed
Solution Approach 1:
The system performs preliminary actions by measuring and recording communication link performance metrics continuously before traffic routing decisions are made. This allows the system to have advance knowledge of link conditions and make more accurate load balancing decisions that account for potential future performance degradation.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring communication link performance and using this information to adjust load balancing decisions. The measured performance metrics are fed back into the load balancing algorithm to dynamically adapt to changing network conditions and prevent routing to degraded links.
2Reliability
If traffic is routed to superior communication links, then connection quality is improved, but network congestion occurs when demand suddenly increases
Solution Approach 1:
The system changes the parameters used for load balancing decisions by incorporating not only current performance metrics but also predicted capacity and idle capacity measurements. This multi-parameter approach allows the system to identify links that can handle sudden demand increases without causing congestion, while still maintaining connection quality.
Solution Approach 2:
The system performs preliminary measurements of link capacity and idle capacity before routing traffic. By knowing the predicted capacity and current idle capacity in advance, the system can proactively route traffic to links that have sufficient headroom, preventing congestion before it occurs rather than reacting after congestion starts.
3Measurement precision
If continuous monitoring of communication links is performed, then load balancing accuracy is improved, but system complexity increases
Solution Approach 1:
The system applies local quality by measuring and monitoring specific local characteristics of each communication link (such as signal-to-noise ratio, carrier-to-noise ratio, and idle capacity) rather than requiring comprehensive global monitoring. This targeted approach achieves accurate load balancing decisions while keeping the monitoring system complexity manageable by focusing only on the most relevant local parameters.
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.