Offline Network Congestion Simulation and Traffic Rerouting
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Solution Overview
Problem
Connection-oriented networks face inefficiencies and congestion due to path selection schemes and limited online routing information, leading to degraded service quality and difficulty in detecting and alleviating congestion without disrupting network operations.
Innovation Solution
The method involves simulating network operations using greedy heuristic processes to identify congested trunks and reroute traffic offline, using a peering server to collect data and an optimization server to generate recommendations for rerouting, thereby alleviating congestion with minimal disruption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If online routing schemes are used with limited routing information, then network operations can proceed in real-time, but congestion detection is delayed and service quality degrades
Solution Approach 1:
The patent performs offline simulations of network routing operations before actual traffic flows occur. By pre-simulating various traffic scenarios and identifying potential congestion points in advance, the system can proactively reroute traffic to avoid congestion before it degrades service quality, thus resolving the contradiction between real-time operation and timely congestion detection.
Solution Approach 2:
The patent introduces an intermediary offline simulation system that acts as a mediator between limited online routing information and congestion detection. The simulation environment processes routing decisions and identifies congestion points without interfering with real-time network operations, allowing accurate congestion detection without compromising service quality or real-time performance.
2Productivity
If traffic is rerouted to alleviate congestion, then network performance improves, but network operations may be disrupted
Solution Approach 1:
The patent performs offline simulations to identify optimal rerouting paths before implementing them in the live network. By pre-calculating rerouting strategies during low-traffic periods or in simulation environments, the system can switch to improved paths with minimal disruption, thus improving network performance while maintaining operational stability.
Solution Approach 2:
The patent implements rerouting gradually rather than all at once. By selectively rerouting only the traffic flows that would most benefit from the new paths while leaving other flows unchanged, the system improves overall network performance without causing widespread disruption to network operations.
3Measurement precision
If comprehensive network data is collected for congestion analysis, then congestion detection accuracy improves, but system complexity and computational load increase
Solution Approach 1:
The patent extracts only the essential routing information and traffic data needed for congestion analysis from the complex network environment. By selectively collecting specific parameters (such as traffic volumes, path utilization, and congestion indicators) rather than all possible network data, the system achieves accurate congestion detection without the complexity and computational burden of comprehensive data collection.
Solution Approach 2:
The patent creates simplified copies of the network topology and traffic patterns in an offline simulation environment. Instead of directly analyzing complex live network data, the system works with replicated models that capture the essential characteristics needed for congestion detection, reducing computational complexity while maintaining detection accuracy.
Data Source
AI summary
Congestion in connection-oriented data networks is alleviated by simulating the rerouting of circuits to uncongested parts of the network and then rerouting such circuits in a manner that causes little, or no, disruption to other parts of the network.