Border Node Routing Across Autonomous Systems
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Solution Overview
Problem
There is a lack of effective mechanisms for routing data across different autonomous systems, particularly when one system involves a software-defined network (SDN), which hinders the satisfaction of quality of service (QoS) requirements due to the incompatibility of existing protocols like BGP with SDNs.
Innovation Solution
A routing optimization mechanism that involves edge nodes in one autonomous system collecting and evaluating real-time network performance information to select an optimal egress edge node for data transmission to a destination node in another autonomous system, even if the topology of the second system is inaccessible, ensuring quality of service by considering current network conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If BGP protocol is used for routing across autonomous systems, then routing decisions can be made based on paths and network policies, but the protocol cannot be used effectively in SDN environments and lacks mechanisms for real-time performance-based routing
Solution Approach 1:
The patent introduces a border node as an intermediary component that bridges traditional BGP routing and SDN-controlled routing. The border node collects real-time performance data from the SDN controller and uses this information to make intelligent routing decisions, effectively mediating between the legacy BGP protocol and the modern SDN architecture to achieve both compatibility and QoS satisfaction
Solution Approach 2:
The system performs preliminary actions by pre-collecting and evaluating real-time performance data before making routing decisions. The border node proactively gathers network performance metrics from the SDN controller and maintains updated performance information, enabling informed routing decisions to be made without delay when data transmission is required
2Reliability
If topology information of the second autonomous system is inaccessible, then security and autonomy are maintained, but conventional routing determination cannot be performed effectively
Solution Approach 1:
The patent implements a feedback mechanism where the border node continuously collects real-time performance data from the SDN controller about the first autonomous system's internal state and uses this feedback to make routing decisions. This internal feedback loop replaces the need for external topology information from the second autonomous system, maintaining security while enabling effective routing through performance-based decision making
Solution Approach 2:
The system practices self-service by using its own internal performance data to make routing decisions. The border node leverages the SDN controller's monitoring capabilities to gather performance metrics within its own autonomous system and uses this self-generated information to determine optimal routes, eliminating dependency on external topology information
3Reliability
If real-time network performance information is collected and evaluated, then superior transmission routes can be determined, but additional complexity is introduced in performance data collection and evaluation
Solution Approach 1:
The border node serves multiple functions: it acts as a BGP speaker for traditional routing, an SDN controller for performance monitoring, a data collector for gathering performance metrics, and a decision-maker for route selection. By consolidating these diverse functions into a single multi-functional component, the patent avoids the complexity that would arise from adding separate dedicated systems for each function
Data Source
AI summary
Systems and methods providing a route optimization mechanism for transmitting data traffic across different autonomous systems based on real-time route performance detection. Regarding a request for routing data between a source node that is coupled to a first autonomous system and a destination node located in a second autonomous system, each of a plurality of edge nodes in the first autonomous system operates to detect and evaluate real-time route performance. The evaluation results are compared and used to select an edge node and an associated link for transporting data between the source node and the destination node. The route optimization mechanism can be adopted in an SDN-based or other virtual network autonomous system.