SDN Controller External Data Adaptation
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Solution Overview
Problem
Software-defined networking faces challenges in dynamically adapting to external changes such as weather conditions and user population distribution, which affect network performance and quality of service, as existing solutions rely primarily on internal data and lack efficient mechanisms for real-time configuration adjustments.
Innovation Solution
A method and system that utilize external weather and population data to generate configuration data for network elements, allowing for dynamic optimization of routing topology and data management policies, and a controller system that receives and processes this information to adapt the network accordingly, using algorithms like heuristic, neural networks, or fuzzy logic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software-defined networking uses traditional IP-based autonomous systems principle for packet forwarding, then the network is simple and scalable, but it cannot adapt to external changes such as weather conditions and user population distribution
Solution Approach 1:
The controller system pre-configures multiple routing topologies and data management policies in advance. When external changes are detected (such as weather conditions or user population shifts), the system can quickly switch between pre-configured options or activate pre-planned adaptation strategies, enabling rapid response without complex real-time decision-making
Solution Approach 2:
The system implements a feedback mechanism where the controller continuously monitors external conditions (weather, user distribution) and internal network performance. Based on this feedback, the controller dynamically adjusts routing topology and data management policies, creating a closed-loop control system that adapts to changing conditions while maintaining manageable complexity through automated control
2Productivity
If the network configuration is changed frequently to adapt to external changes, then the network performance and quality of service improve, but the configuration management becomes more complex and time-consuming
Solution Approach 1:
Multiple routing topologies and data management policies are pre-configured and stored in the controller system. When external changes occur, the system can immediately activate pre-configured solutions rather than creating new configurations from scratch, significantly reducing the time required for configuration adjustments while maintaining high network performance
Solution Approach 2:
The controller system automatically generates and applies configuration changes based on monitored external conditions and performance metrics. This self-service capability eliminates the need for manual configuration management, reducing both the time required for adjustments and the complexity of configuration management while maintaining optimal network performance
Data Source
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Figure 3
AI summary
A method for controlling a software-defined network "SDN" comprises receiving (301) information provided by one or more external sources outside the software-defined network, generating (303) configuration data for changing configuration of one or more network elements of the software-defined network on the basis of the received information in response to a situation (302) where the received information indicates an occurred or forthcoming change of one or more operating conditions of the software-defined network, and sending (304) the configuration data to the network elements so as to adapt the software-defined network to changes of the one or more operating conditions. Therefore, the configuration capabilities provided by the software-defined networking are utilized for dynamically optimizing the software-defined network with respect to changes that are not necessarily indicated by information gathered inside the software-defined network but by information provided by the external sources outside the software-defined network. The figure proposed to be presented with the abstract: Figure 3.