SD-WAN Heat Map Routing for Flow Congestion
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Solution Overview
Problem
Current SD-WAN networks employ static policies, leading to sub-optimal routing and degraded user experience due to the static provisioning of cloud-based transits and secure services, which fail to adapt to the evolving needs of next-generation cloud-native applications.
Innovation Solution
A method is introduced to generate a heat map based on metrics collected from managed forwarding elements (MFEs) in an SD-WAN, which accounts for data message flows, locations of MFEs, and destinations. This heat map is used to identify modifications to the SD-WAN, such as provisioning new MFEs or modifying physical links, to improve forwarding efficiency and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static policies are used for SD-WAN routing, then network stability and reliability are maintained, but forwarding efficiency and user experience degrade due to inability to adapt to changing traffic patterns
Solution Approach 1:
The patent implements dynamic routing policies that automatically adjust based on real-time traffic conditions, service priorities, and network state. The system transitions from static provisioning to dynamic adaptation by continuously monitoring traffic patterns and modifying routing decisions, thereby improving forwarding efficiency while maintaining reliability through controlled adaptation mechanisms.
Solution Approach 2:
The system incorporates feedback loops that monitor traffic flow metrics, user experience indicators, and network performance data. This feedback is used to continuously refine routing decisions and policy adjustments, enabling the network to adapt to changing conditions while maintaining stable operation through iterative optimization.
2Reliability
If cloud-based transits are provisioned close to cloud applications, then service availability is improved, but routing optimization is lost due to static placement decisions
Solution Approach 1:
The patent enables dynamic selection of transit points and routing paths based on real-time conditions. Instead of fixed proximity-based placement, the system can dynamically choose optimal transit locations and routes considering current traffic patterns, network load, and performance requirements, thereby maintaining both availability and optimization.
Solution Approach 2:
The system applies different routing strategies and transit point selections tailored to specific traffic flows, applications, and destination clusters. Each flow can be routed through locally optimal paths rather than using a uniform proximity-based approach, enabling fine-grained optimization while maintaining service availability.
3Reliability
If secure services are statically provisioned as waypoints close to sources, then security requirements are met, but performance degrades due to sub-optimal service placement
Solution Approach 1:
The patent implements dynamic service chaining that can adaptively select and position secure services along traffic flows based on real-time conditions. Instead of fixed source-proximity placement, the system dynamically determines optimal service insertion points considering both security requirements and performance implications, enabling flexible service placement that maintains security while optimizing performance.
Solution Approach 2:
The system introduces intelligent intermediaries that act as adaptive service points between sources and destinations. These intermediaries can dynamically adjust their positioning and functionality to balance security requirements with performance optimization, serving as flexible waypoints rather than fixed infrastructure elements.
4Productivity
If heat map generation and dynamic modifications are implemented, then forwarding efficiency is improved, but system complexity increases due to additional monitoring and analysis components
Solution Approach 1:
The patent integrates heat map generation, traffic analysis, and routing optimization functions into existing SD-WAN control plane components. Rather than adding separate dedicated systems, the solution multi-functionalizes existing elements to perform monitoring, analysis, and decision-making, thereby reducing overall system complexity while achieving dynamic optimization.
Solution Approach 2:
The system implements self-service capabilities where the SD-WAN automatically monitors its own traffic patterns, generates heat maps, and adjusts routing policies without requiring external complex analysis systems. The network self-analyzes and self-optimizes using built-in intelligence, reducing the need for additional external complexity.
Data Source
AI summary
Some embodiments provide a method for modifying an SD-WAN (software-defined wide-area network). The method collects, from a set of managed forwarding elements (MFEs), multiple metrics associated with multiple data message flows sent between the set of MFEs. The method analyzes the collected multiple metrics to group the data message flows according to multiple types and to identify a ranking of the multiple groups of data message flows according to traffic throughput. The method uses the ranking to identify a set of one or more groups of data message flows. The method modifies the SD-WAN to improve forwarding through the SD-WAN for the identified set of one or more groups of data message flows.