SDN Multi-Layer Controller for IP Optical Capacity Planning
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Solution Overview
Problem
Conventional network optimization approaches fail to address joint global optimization of IP and optical layers, leading to inefficient use of resources and increased costs due to separate consideration of traffic routing and lack of dynamic capacity planning in response to network condition changes.
Innovation Solution
A software-defined network multi-layer controller (SDN-MLC) that communicates across multiple layers, using optimization algorithms for near-real-time capacity planning and configuration changes, including the addition or reconfiguration of router cards, optical regenerators, and transponders to ensure sufficient network resources meet quality of service requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If separate optimization approaches are used for IP and optical layers, then device complexity is reduced, but resource efficiency deteriorates and costs increase
Solution Approach 1:
The patent merges the optimization of IP and optical layers into a unified joint global optimization framework. The SDN-MLC controller simultaneously optimizes both layers by considering their interdependencies, where IP routing decisions and optical capacity allocations are made together rather than separately. This integration eliminates the inefficiencies of separate optimization while managing complexity through coordinated control.
Solution Approach 2:
The SDN-MLC controller serves multiple functions: it manages IP layer routing, optimizes optical layer capacity, performs capacity planning, and handles real-time reconfiguration. This multi-functional approach consolidates what would otherwise require separate systems, achieving joint optimization without proportionally increasing device complexity.
2Loss of energy
If joint global optimization is implemented for IP and optical layers, then resource efficiency improves, but device complexity increases
Solution Approach 1:
The SDN-MLC controller acts as an intermediary between the IP and optical layers, managing the complexity of joint optimization. It receives information from both layers, performs coordinated optimization, and implements decisions that affect both layers. This intermediary approach centralizes the complexity in a dedicated control entity rather than distributing it across multiple devices.
Solution Approach 2:
The system performs capacity planning in advance using historical and forecasted data to determine future capacity requirements. By pre-calculating optimal capacity allocations for different time horizons (7, 14, 30 days), the system reduces the complexity of real-time optimization and enables more efficient resource utilization.
3Speed
If capacity planning is performed without forecasting, then response time is reduced, but adaptability to future demands deteriorates
Solution Approach 1:
The system performs preliminary capacity planning by forecasting future traffic demands and pre-determining optimal capacity allocations for multiple time horizons (7, 14, 30 days). This advance planning allows the network to adapt to future demands while maintaining fast response times when actual conditions are reached, as the optimization decisions have already been calculated.
Solution Approach 2:
The system continuously monitors actual network performance and compares it with forecasted conditions, using this feedback to refine future capacity plans. The SDN-MLC controller adjusts capacity allocations based on actual traffic patterns and demand changes, improving adaptability while maintaining efficient response times through iterative optimization.
4Reliability
If installed capacity is increased to meet future demands, then quality of service is improved, but capital expenditures increase
Solution Approach 1:
The system performs advance capacity planning to determine the minimum required capacity for future time horizons (7, 14, 30 days) based on forecasted demand. By calculating optimal capacity requirements beforehand, the network can invest in capacity only when and where it is truly needed, avoiding premature or excessive capital expenditures while ensuring quality of service is maintained.
Solution Approach 2:
The system dynamically adjusts capacity parameters based on actual demand and forecasted conditions. By continuously optimizing capacity allocations and identifying underutilized resources, the system can right-size the network capacity to match actual needs, reducing capital expenditures while maintaining required quality of service levels through efficient resource utilization.
Data Source
AI summary
A software-defined network multi-layer controller (SDN-MLC) may communicate with multiple layers of a telecommunication network. The SDN-MLC may have an optimization algorithm that helps in capacity planning of the telecommunications based on the management of multiple layers of the telecommunication network.