Constraint Optimization for Egress Peer Engineering Traffic Plans
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Solution Overview
Problem
Current network planning and design systems often fail to generate optimized traffic plans, leading to inefficient network operations and wastage of resources due to the lack or incorrect application of traffic engineering techniques.
Innovation Solution
A controller platform utilizes constraint optimization for egress peer engineering to determine and implement optimized traffic plans by analyzing network data, constraints, and costs, thereby assigning traffic to tunnels and peer links efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traffic engineering techniques are not applied or incorrectly applied, then network operations proceed without optimization, but computing and networking resources are wasted due to sub-optimal traffic plans
Solution Approach 1:
The system performs preliminary analysis of network data, constraints, and costs before generating traffic plans. By预先 analyzing the network state and applying constraint optimization algorithms in advance, the system determines optimized traffic plans that prevent resource waste before it occurs, rather than reacting to sub-optimal performance after the fact.
Solution Approach 2:
The system implements a feedback mechanism where network performance data is continuously collected and analyzed. The constraint optimization process uses this feedback to adjust and refine traffic plans, ensuring that computing and networking resources are allocated efficiently based on actual network conditions and performance outcomes.
2Productivity
If constraint optimization is applied to determine traffic assignments, then traffic plans are optimized, but system complexity increases due to processing network data, constraints, and costs
Solution Approach 1:
The constraint optimization process is divided into distinct functional modules: network data processing, constraint modeling, cost analysis, and traffic assignment determination. Each module handles a specific aspect of the optimization problem, making the overall complex system more manageable and maintainable while still achieving optimized traffic plans.
Solution Approach 2:
The controller platform acts as an intermediary between network data collection and traffic plan implementation. It receives network data, applies constraint optimization algorithms, and generates optimized traffic plans, thereby managing the complexity of the optimization process in a centralized and controlled manner without requiring complex distributed processing.
Data Source
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AI summary
A device receives network data associated with a network that includes a peer network with network devices interconnected by links, and receives constraints associated with determining traffic assignments for the network. The device determines traffic and costs associated with the network based on the network data, and determines traffic assignments based on the traffic and the costs associated with the network, the constraints, and a model for the constraints. The device determines tunnel use based on the traffic assignments, and determines peer link use based on the tunnel use. The device determines costs associated with the traffic assignments, the tunnel use, and the peer link use for the network, and generates traffic plans based on the traffic assignments, the tunnel use, the peer link use, and the costs. The device causes one of the traffic plans to be implemented in the network by the network devices and the links.