Intelligent Routing vs. Processing Overhead
Implement hierarchical routing intelligence, reserving computationally intensive optimisation for periodic or event-driven recalculation rather than continuous processing.
CyberTRIZ analysis · Telecommunications contradiction TA019 · one of 8,235 worked contradictions published by CyberTRIZ.AI
Regulations
Business Context
Intelligent routing can improve latency, congestion management, reliability, energy efficiency, and service quality by considering richer information than conventional static routing. The more variables the system evaluates, however, the more processing, telemetry, state synchronization, and decision time it requires. Excessive intelligence can reduce the efficiency it is intended to improve.
Telecommunications TRIZ Resolution
Routing intelligence should be hierarchical. Fast local decisions can use limited variables, while deeper optimization occurs periodically or when significant conditions change. Precomputed paths, policy constraints, summarized network state, and event-driven recalculation can reduce processing without sacrificing useful intelligence.
Applicable TRIZ Principles
Principle 1 – Segmentation separates fast routing decisions from computationally intensive optimization.
Principle 10 – Prior Action precomputes viable routes before urgent decisions are needed.
Principle 19 – Periodic Action performs deeper optimization at selected intervals rather than continuously.
Expected Outcome
Smarter traffic routing
Lower processing overhead
Faster routing decisions
Improved network scalability
Decision Indicators
Early indicators include:
Routing optimization consumes significant control-plane resources.
Decision latency increases as more network variables are included.
Frequent recalculation provides little additional performance benefit.
Central optimization struggles to maintain current network state.
Routing intelligence scales poorly as network size grows.